Methods and compositions for selecting sirna of improved functionality

ABSTRACT

Efficient sequence specific gene silencing is possible through the use of siRNA technology. By selecting particular siRNAs by rational design, one can maximize the generation of an effective gene silencing reagent, as well as methods for silencing genes. Methods, compositions, and kits generated through rational design of siRNAs are disclosed.

REFERENCE TO TABLES SUBMITTED IN ELECTRONIC FORM

In accordance with PCT Administrative Instructions Part 8, Applicant submits a compact disc of tables related to sequences and hereby incorporates by reference the material submitted herewith, on the compact disk labeled COPY 1—TABLES PART DISK 1/1, TABLES XII and XIII (provided in triplicate, which copies are identical), in files entitled table-xii.txt, date of creation 26 Apr. 2004, with a size of 110,486 kb, and table-xiii.txt, date of creation 26 Apr. 2004, with a size of 23,146 kb; and in accordance with PCT Administrative Instructions Section 801(a)(i) on the compact disk labeled CRF (with three further copies, which copies are identical) in a file entitled 13608PCT.txt, date of creation 26 Apr. 2004, with a size of 556,776 kb.

FIELD OF INVENTION

The present invention relates to RNA interference (“RNAi”).

BACKGROUND OF THE INVENTION

Relatively recently, researchers observed that double stranded RNA (“dsRNA”) could be used to inhibit protein expression. This ability to silence a gene has broad potential for treating human diseases, and many researchers and commercial entities are currently investing considerable resources in developing therapies based on this technology.

Double stranded RNA induced gene silencing can occur on at least three different levels: (i) transcription inactivation, which refers to RNA guided DNA or histone methylation; (ii) siRNA induced mRNA degradation; and (iii) mRNA induced transcriptional attenuation.

It is generally considered that the major mechanism of RNA induced silencing (RNA interference, or RNAi) in mammalian cells is mRNA degradation. Initial attempts to use RNAi in mammalian cells focused on the use of long strands of dsRNA. However, these attempts to induce RNAi met with limited success, due in part to the induction of the interferon response, which results in a general, as opposed to a target-specific, inhibition of protein synthesis. Thus, long dsRNA is not a viable option for RNAi in mammalian systems.

More recently it has been shown that when short (18-30 bp) RNA duplexes are introduced into mammalian cells in culture, sequence-specific inhibition of target mRNA can be realized without inducing an interferon response. Certain of these short dsRNAs, referred to as small inhibitory RNAs (“siRNAs”), can act catalytically at sub-molar concentrations to cleave greater than 95% of the target mRNA in the cell. A description of the mechanisms for siRNA activity, as well as some of its applications are described in Provost et al., Ribonuclease Activity and RNA Binding of Recombinant Human Dicer, E.M.B.O. J., 2002 Nov. 1; 21(21): 5864-5874; Tabara et al., The dsRNA Binding Protein RDE-4 Interacts with RDE-1, DCR-1 and a DexH-box Helicase to Direct RNAi in C. elegans, Cell 2002, Jun. 28;109(7):861-71; Ketting et al., Dicer Functions in RNA Interference and in Synthesis of Small RNA Involved in Developmental Timing in C. elegans; Martinez et al., Single-Stranded Antisense siRNAs Guide Target RNA Cleavage in RNAi, Cell 2002, Sep. 6; 110(5):563; Hutvagner & Zamore, A micro RNA in a multiple-turnover RNAi enzyme complex, Science 2002, 297:2056.

From a mechanistic perspective, introduction of long double stranded RNA into plants and invertebrate cells is broken down into siRNA by a Type III endonuclease known as Dicer. Sharp, RNA interference—2001, Genes Dev. 2001, 15:485. Dicer, a ribonuclease-III-like enzyme, processes the dsRNA into 19-23 base pair short interfering RNAs with characteristic two base 3′ overhangs. Bernstein, Caudy, Hammond, & Hannon, Role for a bidentate ribonuclease in the initiation step of RNA interference, Nature 2001, 409:363. The siRNAs are then incorporated into an RNA-induced silencing complex (RISC) where one or more helicases unwind the siRNA duplex, enabling the complementary antisense strand to guide target recognition. Nykanen, Haley, & Zamore, ATP requirements and small interfering RNA structure in the RNA interference pathway, Cell 2001, 107:309. Upon binding to the appropriate target mRNA, one or more endonucleases within the RISC cleaves the target to induce silencing. Elbashir, Lendeckel, & Tuschl, RNA interference is mediated by 21- and 22-nucleotide RNAs, Genes Dev 2001, 15:188, FIG. 1.

The interference effect can be long lasting and may be detectable after many cell divisions. Moreover, RNAi exhibits sequence specificity. Kisielow, M. et al. (2002) Isoform-specific knockdown and expression of adaptor protein ShcA using small interfering RNA, J. of Biochemistry 363: 1-5. Thus, the RNAi machinery can specifically knock down one type of transcript, while not affecting closely related mRNA. These properties make siRNA a potentially valuable tool for inhibiting gene expression and studying gene function and drug target validation. Moreover, siRNAs are potentially useful as therapeutic agents against: (1) diseases that are caused by over-expression or misexpression of genes; and (2) diseases brought about by expression of genes that contain mutations.

Successful siRNA-dependent gene silencing depends on a number of factors. One of the most contentious issues in RNAi is the question of the necessity of siRNA design, i.e., considering the sequence of the siRNA used. Early work in C. elegans and plants circumvented the issue of design by introducing long dsRNA (see, for instance, Fire, A. et al. (1998) Nature 391:806-811). In this primitive organism, long dsRNA molecules are cleaved into siRNA by Dicer, thus generating a diverse population of duplexes that can potentially cover the entire transcript. While some fraction of these molecules are non-functional (i.e., induce little or no silencing) one or more have the potential to be highly functional, thereby silencing the gene of interest and alleviating the need for siRNA design. Unfortunately, due to the interferon response, this same approach is unavailable for mammalian systems. While this effect can be circumvented by bypassing the Dicer cleavage step and directly introducing siRNA, this tactic carries with it the risk that the chosen siRNA sequence may be non-functional or semi-functional.

A number of researches have expressed the view that siRNA design is not a crucial element of RNAi. On the other hand, others in the field have begun to explore the possibility that RNAi can be made more efficient by paying attention to the design of the siRNA. Unfortunately, none of the reported methods have provided a satisfactory scheme for reliably selecting siRNA with acceptable levels of functionality. Accordingly, there is a need to develop rational criteria by which to select siRNA with an acceptable level of functionality, and to identify siRNA that have this improved level of functionality, as well as to identify siRNAs that are hyperfunctional.

SUMMARY OF THE INVENTION

The present invention is directed to increasing the efficiency of RNAi, particularly in mammalian systems. Accordingly, the present invention provides kits, siRNAs and methods for increasing siRNA efficacy.

According to a first embodiment, the present invention provides a kit for gene silencing, wherein said kit is comprised of a pool of at least two siRNA duplexes, each of which is comprised of a sequence that is complementary to a portion of the sequence of one or more target messenger RNA, and each of which is selected using non-target specific criteria.

According to a second embodiment, the present invention provides a method for selecting an siRNA, said method comprising applying selection criteria to a set of potential siRNA that comprise 18-30 base pairs, wherein said selection criteria are non-target specific criteria, and said set comprises at least two siRNAs and each of said at least two siRNAs contains a sequence that is at least substantially complementary to a target gene; and determining the relative functionality of the at least two siRNAs.

In one embodiment, the present invention also provides a method wherein said selection criteria are embodied in a formula comprising: (−14)*G₁₃−13*A₁−12*U₇−11*U₂−10*A₁₁−10*U₄−10*C₃−10*C₅−10*C₆−9*A₁₀−9*U₉−9*C₁₈−8*G₁₀−7*U₁−7*U₁₆−7*C₁₇−7*C₁₉+7*U₁₇+8*A₂+8*A₄+8*A₅+8*C₄+9*G₈+10*A₇+10*U₁₈+11*A₁₉+11*C₉+15*G₁+18*A₃+19*U₁₀−Tm−3* (GC_(total))−6*(GC₁₅₋₁₉)−30*X; or   Formula VIII (−8)*A1+(−1)*A2+(12)*A3+(7)*A4+(18)*A5+(12)*A6+(19)*A7+(6)*A8+(−4)*A9+(−5)*A10+(−2)*A11+(−5)*A12+(17)*A13+(−3)*A14+(4)*A15+(2)*A16+(8)*A17+(11)*A18+(30)*A19+(−13)*U1+(−10)*U2+(2)*U3+(−2)*U4+(−5)*U5+(5)*U6+(−2)*U7+(−10)*U8+(−5)*U9+(15)*U10+(−1)*U11+(0)*U12+(10)*U13+(−9)*U14+(−13)*U15+(−10)*U16+(3)*U17+(9)*U18+(9)*U19+(7)*C1+(3)*C2+(−21)*C3+(5)*C4+(−9)*C5+(−20)*C6+(−18)*C7+(−5)*C8+(5)*C9+(1)*C10+(2)*C11+(−5)*C12+(−3)*C13+(−6)*C14+(−2)*C15+(−5)*C16+(−3)*C17+(−12)*C18+(−18)*C19+(14)*G1+(8)*G2+(7)*G3+(−10)*G4+(−4)*G5+(2)*G6+(1)*G7+(9)*G8+(5)*G9+(−11)*G10+(1)*G11+(9)*G12+(−24)*G13+(18)*G14+(11)*G15+(13)*G16+(−7)*G17+(−9)*G18+(−22)*G19+6*(number of A+U in position 15-19)−3*(number of G+C in whole siRNA),   Formula X wherein position numbering begins at the 5′-most position of a sense strand, and

-   -   A₁=1 if A is the base at position 1 of the sense strand,         otherwise its value is 0;     -   A₂=1 if A is the base at position 2 of the sense strand,         otherwise its value is 0;     -   A₃=1 if A is the base at position 3 of the sense strand,         otherwise its value is 0;     -   A₄=1 if A is the base at position 4 of the sense strand,         otherwise its value is 0;     -   A₅=1 if A is the base at position 5 of the sense strand,         otherwise its value is 0;     -   A₆=1 if A is the base at position 6 of the sense strand,         otherwise its value is 0;     -   A₇=1 if A is the base at position 7 of the sense strand,         otherwise its value is 0;     -   A₁₀=1 if A is the base at position 10 of the sense strand,         otherwise its value is 0;     -   A₁₁=1 if A is the base at position 11 of the sense strand,         otherwise its value is 0;     -   A₁₃=1 if A is the base at position 13 of the sense strand,         otherwise its value is 0;     -   A₁₉=1 if A is the base at position 19 of the sense strand,         otherwise if another base is present or the sense strand is only         18 base pairs in length, its value is 0;     -   C₃=1 if C is the base at position 3 of the sense strand,         otherwise its value is 0;     -   C₄=1 if C is the base at position 4 of the sense strand,         otherwise its value is 0;     -   C₅=1 if C is the base at position 5 of the sense strand,         otherwise its value is 0;     -   C₆=1 if C is the base at position 6 of the sense strand,         otherwise its value is 0;     -   C₇=1 if C is the base at position 7 of the sense strand,         otherwise its value is 0;     -   C₉=1 if C is the base at position 9 of the sense strand,         otherwise its value is 0;     -   C₁₇=1 if C is the base at position 17 of the sense strand,         otherwise its value is 0;     -   C₁₈=1 if C is the base at position 18 of the sense strand,         otherwise its value is 0;     -   C₁₉=1 if C is the base at position 19 of the sense strand,         otherwise if another base is present or the sense strand is only         18 base pairs in length, its value is 0;     -   G₁=1 if G is the base at position 1 on the sense strand,         otherwise its value is 0;     -   G₂=1 if G is the base at position 2 of the sense strand,         otherwise its value is 0;     -   G₈=1 if G is the base at position 8 on the sense strand,         otherwise its value is 0;     -   G₁₀=1 if G is the base at position 10 on the sense strand,         otherwise its value is 0;     -   G₁₃=1 if G is the base at position 13 on the sense strand,         otherwise its value is 0;     -   G₁₉=1 if G is the base at position 19 of the sense strand,         otherwise if another base is present or the sense strand is only         18 base pairs in length, its value is 0;     -   U₁=1 if U is the base at position 1 on the sense strand,         otherwise its value is 0;     -   U₂=1 if U is the base at position 2 on the sense strand,         otherwise its value is 0;     -   U₃=1 if U is the base at position 3 on the sense strand,         otherwise its value is 0;     -   U₄=1 if U is the base at position 4 on the sense strand,         otherwise its value is 0;     -   U₇=1 if U is the base at position 7 on the sense strand,         otherwise its value is 0;     -   U₉=1 if U is the base at position 9 on the sense strand,         otherwise its value is 0;     -   U₁₀=1 if U is the base at position 10 on the sense strand,         otherwise its value is 0;     -   U₁₅=1 if U is the base at position 15 on the sense strand,         otherwise its value is 0;     -   U₁₆=1 if U is the base at position 16 on the sense strand,         otherwise its value is 0;     -   U₁₇=1 if U is the base at position 17 on the sense strand,         otherwise its value is 0;     -   U₁₈=1 if U is the base at position 18 on the sense strand,         otherwise its value is 0.     -   GC₁₅₋₁₉=the number of G and C bases within positions 15-19 of         the sense strand, or within positions 15-18 if the sense strand         is only 18 base pairs in length;     -   GC_(total)=the number of G and C bases in the sense strand;     -   Tm=100 if the siRNA oligo has the internal repeat longer then 4         base pairs, otherwise its value is 0; and     -   X=the number of times that the same nucleotide repeats four or         more times in a row.

According to a third embodiment, the invention provides a method for developing an algorithm for selecting siRNA, said method comprising: (a) selecting a set of siRNA; (b) measuring gene silencing ability of each siRNA from said set; (c) determining relative functionality of each siRNA; (d) determining improved functionality by the presence or absence of at least one variable selected from the group consisting of the presence or absence of a particular nucleotide at a particular position, the total number of As and Us in positions 15-19, the number of times that the same nucleotide repeats within a given sequence, and the total number of Gs and Cs; and (e) developing an algorithm using the information of step (d).

According to a fourth embodiment, the present invention provides a kit, wherein said kit is comprised of at least two siRNAs, wherein said at least two siRNAs comprise a first optimized siRNA and a second optimized siRNA, wherein said first optimized siRNA and said second optimized siRNA are optimized according a formula comprising Formula X.

According to a fifth embodiment, the present invention provides a method for identifying a hyperfunctional siRNA, comprising applying selection criteria to a set of potential siRNA that comprise 18-30 base pairs, wherein said selection criteria are non-target specific criteria, and said set comprises at least two siRNAs and each of said at least two siRNAs contains a sequence that is at least substantially complementary to a target gene; determining the relative functionality of the at least two siRNAs and assigning each of the at least two siRNAs a functionality score; and selecting siRNAs from the at least two siRNAs that have a functionality score that reflects greater than 80 percent silencing at a concentration in the picomolar range, wherein said greater than 80 percent silencing endures for greater than 120 hours.

According to a sixth embodiment, the present invention provides a hyperfunctional siRNA that is capable of silencing Bc12.

According to a seventh embodiment, the present invention provides a method for developing an siRNA algorithm for selecting functional and hyperfunctional siRNAs for a given sequence. The method comprises:

-   -   (a) selecting a set of siRNAs;     -   (b) measuring the gene silencing ability of each siRNA from said         set;     -   (c) determining the relative functionality of each siRNA;     -   (d) determining the amount of improved functionality by the         presence or absence of at least one variable selected from the         group consisting of the total GC content, melting temperature of         the siRNA, GC content at positions 15-19, the presence or         absence of a particular nucleotide at a particular position,         relative thermodynamic stability at particular positions in a         duplex, and the number of times that the same nucleotide repeats         within a given sequence; and     -   (e) developing an algorithm using the information of step (d).         According to this embodiment, preferably the set of siRNAs         comprises at least 90 siRNAs from at least one gene, more         preferably at least 180 siRNAs from at least two different         genes, and most preferably at least 270 and 360 siRNAs from at         least three and four different genes, respectively.         Additionally, in step (d) the determination is made with         preferably at least two, more preferably at least three, even         more preferably at least four, and most preferably all of the         variables. The resulting algorithm is not target sequence         specific.

In another embodiment, the present invention provides rationally designed siRNAs identified using the formulas above.

In yet another embodiment, the present invention is directed to hyperfunctional siRNA.

The ability to use the above algorithms, which are not sequence or species specific, allows for the cost-effective selection of optimized siRNAs for specific target sequences. Accordingly, there will be both greater efficiency and reliability in the use of siRNA technologies.

For a better understanding of the present invention together with other and further advantages and embodiments, reference is made to the following description taken in conjunction with the examples, the scope of which is set forth in the appended claims.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 shows a model for siRNA-RISC interactions. RISC has the ability to interact with either end of the siRNA or miRNA molecule. Following binding, the duplex is unwound, and the relevant target is identified, cleaved, and released.

FIG. 2 is a representation of the functionality of two hundred and seventy siRNA duplexes that were generated to target human cyclophilin, human diazepam-binding inhibitor (DB), and firefly luciferase.

FIG. 3 a is a representation of the silencing effect of 30 siRNAs in three different cells lines, HEK293, DU145, and Hela. FIG. 3 b shows the frequency of different functional groups (>95% silencing (black), >80% silencing (gray), >50% silencing (dark gray), and <50% silencing (white)) based on GC content. In cases where a given bar is absent from a particular GC percentage, no siRNA were identified for that particular group. FIG. 3 c shows the frequency of different functional groups based on melting temperature (Tm).

FIG. 4 is a representation of a statistical analysis that revealed correlations between silencing and five sequence-related properties of siRNA: (A) an A at position 19 of the sense strand, (B) an A at position 3 of the sense strand, (C) a U at position 10 of the sense strand, (D) a base other than G at position 13 of the sense strand, and (E) a base other than C at position 19 of the sense strand. All variables were correlated with siRNA silencing of firefly luciferase and human cyclophilin. siRNAs satisfying the criterion are grouped on the left (Selected) while those that do not, are grouped on the right (Eliminated). Y-axis is “% Silencing of Control.” Each position on the X-axis represents a unique siRNA.

FIGS. 5A and 5B are representations of firefly luciferase and cyclophilin siRNA panels sorted according to functionality and predicted values using Formula VIII. The siRNA found within the circle represent those that have Formula VIII values (SMARTscores™) above zero. siRNA outside the indicated area have calculated Formula VIII values that are below zero. Y-axis is “Expression (% Control).” Each position on the X-axis represents a unique siRNA.

FIG. 6A is a representation of the average internal stability profile (AISP) derived from 270 siRNAs taken from three separate genes (cyclophilin B, DBI and firefly luciferase). Graphs represent AISP values of highly functional, functional, and non-functional siRNA. FIG. 6B is a comparison between the AISP of naturally derived GFP siRNA (filled squares) and the AISP of siRNA from cyclophilin B, DBI, and luciferase having >90% silencing properties (no fill) for the antisense strand. “DG” is the symbol for ΔG, free energy.

FIG. 7 is a histogram showing the differences in duplex functionality upon introduction of basepair mismatches. The X-axis shows the mismatch introduced in the siRNA and the position it is introduced (e.g., 8C>A reveals that position 8 (which normally has a C) has been changed to an A). The Y-axis is “% Silencing (Normalized to Control).”

FIG. 8 a is histogram that shows the effects of 5′ sense and antisense strand modification with 2′-O-methylation on functionality. FIG. 8 b is an expression profile showing a comparison of sense strand off-target effects for IGF1R-3 and 2′-O-methyl IGF1R-3. Sense strand off-targets (lower box) are not induced when the 5′ end of the sense strand is modified with 2′-O-methyl groups (top box).

FIG. 9 shows a graph of SMARTscores™ versus RNAi silencing values for more than 360 siRNA directed against 30 different genes. siRNA to the right of the vertical bar represent those siRNA that have desirable SMARTscores™.

FIGS. 10A-E compare the RNAi of five different genes (SEAP, DBI, PLK, Firefly Luciferase, and Renila Luciferase) by varying numbers of randomly selected siRNA and four rationally designed (SMART-selected) siRNA chosen using the algorithm described in Formula VIII. In addition, RNAi induced by a pool of the four SMART-selected siRNA is reported at two different concentrations (100 and 400 nM). 10F is a comparison between a pool of randomly selected EGFR siRNA (Pool 1) and a pool of SMART selected EGFR siRNA (Pool 2). Pool 1, S1-S4 and Pool 2 S1-S4 represent the individual members that made up each respective pool. Note that numbers for random siRNAs represent the position of the 5′ end of the sense strand of the duplex. The Y-axis represents the % expression of the control(s). The X-axis is the percent expression of the control.

FIG. 11 shows the Western blot results from cells treated with siRNA directed against twelve different genes involved in the clathrin-dependent endocytosis pathway (CHC, DynII, CALM, CLCa, CLCb, Eps15, Eps15R, Rab5a, Rab5b, Rab5c, β2 subunit of AP-2 and EEA.1). siRNA were selected using Formula VIII. “Pool” represents a mixture of duplexes 1-4. Total concentration of each siRNA in the pool is 25 nM. Total concentration=4×25=100 nM.

FIG. 12 is a representation of the gene silencing capabilities of rationally-selected siRNA directed against ten different genes (human and mouse cyclophilin, C-myc, human lamin A/C, QB (ubiquinol-cytochrome c reductase core protein I), MEK1 and MEK2, ATE1 (arginyl-tRNA protein transferase), GAPDH, and Eg5). The Y-axis is the percent expression of the control. Numbers 1, 2, 3 and 4 represent individual rationally selected siRNA. “Pool” represents a mixture of the four individual siRNA.

FIG. 13 is the sequence of the top ten Bcl2 siRNAs as determined by Formula VIII. Sequences are listed 5′ to 3′.

FIG. 14 is the knockdown by the top ten Bcl2 siRNAs at 100 nM concentrations. The Y-axis represents the amount of expression relative to the non-specific (ns) and transfection mixture control.

FIG. 15 represents a functional walk where siRNA beginning on every other base pair of a region of the luciferase gene are tested for the ability to silence the luciferase gene. The Y-axis represents the percent expression relative to a control. The X-axis represents the position of each individual siRNA.

FIG. 16 is a histogram demonstrating the inhibition of target gene expression by pools of 2 and 3 siRNAs duplexes taken from the walk described in FIG. 15. The Y-axis represents the percent expression relative to control. The X-axis represents the position of the first siRNA in paired pools, or trios of siRNA. For instance, the first paired pool contains siRNA 1 and 3. The second paired pool contains siRNA 3 and 5. Pool 3 (of paired pools) contains siRNA 5 and 7, and so on.

FIG. 17 is a histogram demonstrating the inhibition of target gene expression by pools of 4 and 5 siRNA duplexes. The Y-axis represents the percent expression relative to a control. The X-axis represents the position of the first siRNA in each pool.

FIG. 18 is a histogram demonstrating the inhibition of target gene expression by siRNAs that are ten and twenty basepairs apart. The Y-axis represents the percent expression relative to a control. The X-axis represents the position of the first siRNA in each pool.

FIG. 19 shows that pools of siRNAs (dark gray bar) work as well (or better) than the best siRNA in the pool (light gray bar). The Y-axis represents the percent expression relative to a control. The-X axis represents the position of the first siRNA in each pool.

FIG. 20 shows that the combination of several semifunctional siRNAs (dark gray) result in a significant improvement of gene expression inhibition over individual (semi-functional; light gray) siRNA. The Y-axis represents the percent expression relative to a control.

FIG. 21 shows both pools (Library, Lib) and individual siRNAs in inhibition of gene expression of Beta-Galactosidase, Renilla Luciferase and SEAP (alkaline phosphatase). Numbers on the X-axis indicate the position of the 5′-most nucleotide of the sense strand of the duplex. The Y-axis represents the percent expression of each gene relative to a control. Libraries contain 19 nucleotide long siRNAs (not including overhangs) that begin at the following nucleotides: SEAP: Lib 1: 206, 766, 812,923, Lib 2: 1117, 1280, 1300, 1487, Lib 3: 206, 766, 812, 923, 1117, 1280, 1300,1487, Lib 4: 206, 812, 1117, 1300, Lib 5: 766, 923, 1280, 1487, Lib 6: 206, 1487; Bgal: Lib 1: 979, 1339, 2029, 2590, Lib 2: 1087,1783,2399,3257, Lib 3: 979, 1783, 2590, 3257, Lib 4: 979, 1087, 1339, 1783, 2029, 2399,2590,3257, Lib 5: 979, 1087, 1339, 1783, Lib 6: 2029,2399,2590,3257; Renilla: Lib 1: 174,300,432,568, Lib 2: 592, 633, 729,867, Lib 3: 174, 300, 432, 568, 592, 633,729,867, Lib 4: 174, 432, 592, 729, Lib 5: 300,568,633,867, Lib 6: 592,568.

FIG. 22 shows the results of an EGFR and TfnR internalization assay when single gene knockdowns are performed. The Y-axis represents percent internalization relative to control.

FIG. 23 shows the results of an EGFR and TfnR internalization assay when multiple genes are knocked down (e.g., Rab5a, b, c). The Y-axis represents the percent internalization relative to control.

FIG. 24 shows the simultaneous knockdown of four different genes. siRNAs directed against G6PD, GAPDH, PLK, and UQCwere simultaneously introduced into cells. Twenty-four hours later, cultures were harvested and assayed for mRNA target levels for each of the four genes. A comparison is made between cells transfected with individual siRNAs vs. a pool of siRNAs directed against all four genes.

FIG. 25 shows the functionality of ten siRNAs at 0.3 nM concentrations.

DETAILED DESCRIPTION DEFINITIONS

Unless stated otherwise, the following terms and phrases have the meanings provided below:

siRNA

The term “siRNA” refers to small inhibitory RNA duplexes that induce the RNA interference (RNAi) pathway. These molecules can vary in length (generally 18-30 basepairs) and contain varying degrees of complementarity to their target mRNA in the antisense strand. Some, but not all, siRNA have unpaired overhanging bases on the 5′ or 3′ end of the sense strand and/or the antisense strand. The term “siRNA” includes duplexes of two separate strands, as well as single strands that can form hairpin structures comprising a duplex region.

siRNA may be divided into five (5) groups (non-functional, semi-functional, functional, highly functional, and hyper-functional) based on the level or degree of silencing that they induce in cultured cell lines. As used herein, these definitions are based on a set of conditions where the siRNA is transfected into said cell line at a concentration of 100 nM and the level of silencing is tested at a time of roughly 24 hours after transfection, and not exceeding 72 hours after transfection. In this context, “non-functional siRNA” are defined as those siRNA that induce less than 50% (<50%) target silencing. “Semi-functional siRNA” induce 50-79% target silencing. “Functional siRNA” are molecules that induce 80-95% gene silencing. “Highly-functional siRNA” are molecules that induce greater than 95% gene silencing. “Hyperfunctional siRNA” are a special class of molecules. For purposes of this document, hyperfunctional siRNA are defined as those molecules that: (1) induce greater than 95% silencing of a specific target when they are transfected at subnanomolar concentrations (i.e., less than one nanomolar); and/or (2) induce functional (or better) levels of silencing for greater than 96 hours. These relative functionalities (though not intended to be absolutes) may be used to compare siRNAs to a particular target for applications such as functional genomics, target identification and therapeutics.

miRNA

The term “miRNA” refers to microRNA.

Gene Silencing

The phrase “gene silencing” refers to a process by which the expression of a specific gene product is lessened or attenuated. Gene silencing can take place by a variety of pathways. Unless specified otherwise, as used herin, gene silencing refers to decreases in gene product expression that results from RNA interference (RNAi), a defined, though partially characterized pathway whereby small inhibitory RNA (siRNA) act in concert with host proteins (e.g., the RNA induced silencing complex, RISC) to degrade messenger RNA (mRNA) in a sequence-dependent fashion. The level of gene silencing can be measured by a variety of means, including, but not limited to, measurement of transcript levels by Northern Blot Analysis, B-DNA techniques, transcription-sensitive reporter constructs, expression profiling (e.g., DNA chips), and related technologies. Alternatively, the level of silencing can be measured by assessing the level of the protein encoded by a specific gene. This can be accomplished by performing a number of studies including Western Analysis, measuring the levels of expression of a reporter protein that has e.g., fluorescent properties (e.g., GFP) or enzymatic activity (e.g., alkaline phosphatases), or several other procedures.

Filters

The term “filter” refers to one or more procedures that are performed on sequences that are identified by the algorithm. In some instances, filtering includes in silico procedures where sequences identified by the algorithm can be screened to identify duplexes carrying desirable or undesirable motifs. Sequences carrying such motifs can be selected for, or selected against, to obtain a final set with the preferred properties. In other instances, filtering includes wet lab experiments. For instance, sequences identified by one or more versions of the algorithm can be screened using any one of a number of procedures to identify duplexes that have hyperfunctional traits (e.g., they exhibit a high degree of silencing at subnanomolar concentrations and/or exhibit high degrees of silencing longevity).

Transfection

The term “transfection” refers to a process by which agents are introduced into a cell. The list of agents that can be transfected is large and includes, but is not limited to, siRNA, sense and/or anti-sense sequences, DNA encoding one or more genes and organized into an expression plasmid, proteins, protein fragments, and more. There are multiple methods for transfecting agents into a cell including, but not limited to, electroporation, calcium phosphate-based transfections, DEAE-dextran-based transfections, lipid-based transfections, molecular conjugate-based transfections (e.g., polylysine-DNA conjugates), microinjection and others.

Target

The term “target” is used in a variety of different forms throughout this document and is defined by the context in which it is used. “Target mRNA” refers to a messenger RNA to which a given siRNA can be directed against. “Target sequence” and “target site” refer to a sequence within the mRNA to which the sense strand of an siRNA shows varying degrees of homology and the antisense strand exhibits varying degrees of complementarity. The phrase “siRNA target” can refer to the gene, mRNA, or protein against which an siRNA is directed. Similarly, “target silencing” can refer to the state of a gene, or the corresponding mRNA or protein.

Off-Target Silencing and Off-Target Interference

The phrases “off-target silencing” and “off-target interference” are defined as degradation of mRNA other than the intended target mRNA due to overlapping and/or partial homology with secondary mRNA messages.

SMARTscore™

The term “SMARTscore™” refers to a number determined by applying any of the Formulas I-Formula X to a given siRNA sequence. The phrases “SMART-selected” or “rationally selected” or “rational selection” refer to siRNA that have been selected on the basis of their SMARTscores™.

Complementary

The term “complementary” refers to the ability of polynucleotides to form base pairs with one another. Base pairs are typically formed by hydrogen bonds between nucleotide units in antiparallel polynucleotide strands. Complementary polynucleotide strands can base pair in the Watson-Crick manner (e.g., A to T, A to U, C to G), or in any other manner that allows for the formation of duplexes. As persons skilled in the art are aware, when using RNA as opposed to DNA, uracil rather than thymine is the base that is considered to be complementary to adenosine. However, when a U is denoted in the context of the present invention, the ability to substitute a T is implied, unless otherwise stated.

Perfect complementarity or 100% complementarity refers to the situation in which each nucleotide unit of one polynucleotide strand can hydrogen bond with a nucleotide unit of a second polynucleotide strand. Less than perfect complementarity refers to the situation in which some, but not all, nucleotide units of two strands can hydrogen bond with each other. For example, for two 20-mers, if only two base pairs on each strand can hydrogen bond with each other, the polynucleotide strands exhibit 10% complementarity. In the same example, if 18 base pairs on each strand can hydrogen bond with each other, the polynucleotide strands exhibit 90% complementarity. “Substantial complementarity” refers to polynucleotide strands exhibiting 79% or greater complementarity, excluding regions of the polynucleotide strands, such as overhangs, that are selected so as to be noncomplementary. (“Substantial similarity” refers to polynucleotide strands exhibiting 79% or greater similarity, excluding regions of the polynucleotide strands, such as overhangs, that are selected so as not to be similar.) Thus, for example, two polynucleotides of 29 nucleotide units each, wherein each comprises a di-dT at the 3′ terminus such that the duplex region spans 27 bases, and wherein 26 of the 27 bases of the duplex region on each strand are complementary, are substantially complementary since they are 96.3% complementary when excluding the di-dT overhangs.

Deoxynucleotide

The term “deoxynucleotide” refers to a nucleotide or polynucleotide lacking a hydroxyl group (OH group) at the 2′ and/or 3′ position of a sugar moiety. Instead, it has a hydrogen bonded to the 2′ and/or 3′ carbon. Within an RNA molecule that comprises one or more deoxynucleotides, “deoxynucleotide” refers to the lack of an OH group at the 2′ position of the sugar moiety, having instead a hydrogen bonded directly to the 2′ carbon.

Deoxyribonucleotide

The terms “deoxyribonucleotide” and “DNA” refer to a nucleotide or polynucleotide comprising at least one sugar moiety that has an H, rather than an OH, at its 2′ and/or 3′ position.

Substantially Similar

The phrase “substantially similar” refers to a similarity of at least 90% with respect to the identity of the bases of the sequence.

Duplex Region

The phrase “duplex region” refers to the region in two complementary or substantially complementary polynucleotides that form base pairs with one another, either by Watson-Crick base pairing or any other manner that allows for a stabilized duplex between polynucleotide strands that are complementary or substantially complementary. For example, a polynucleotide strand having 21 nucleotide units can base pair with another polynucleotide of 21 nucleotide units, yet only 19 bases on each strand are complementary or substantially complementary, such that the “duplex region” has 19 base pairs. The remaining bases may, for example, exist as 5′ and 3′ overhangs. Further, within the duplex region, 100% complementarity is not required; substantial complementarity is allowable within a duplex region. Substantial complementarity refers to 79% or greater complementarity. For example, a mismatch in a duplex region consisting of 19 base pairs results in 94.7% complementarity, rendering the duplex region substantially complementary.

Nucleotide

The term “nucleotide” refers to a ribonucleotide or a deoxyribonucleotide or modified form thereof, as well as an analog thereof. Nucleotides include species that comprise purines, e.g., adenine, hypoxanthine, guanine, and their derivatives and analogs, as well as pyrimidines, e.g., cytosine, uracil, thymine, and their derivatives and analogs.

Nucleotide analogs include nucleotides having modifications in the chemical structure of the base, sugar and/or phosphate, including, but not limited to, 5-position pyrimidine modifications, 8-position purine modifications, modifications at cytosine exocyclic amines, and substitution of 5-bromo-uracil; and 2′-position sugar modifications, including but not limited to, sugar-modified ribonucleotides in which the 2′—OH is replaced by a group such as an H, OR, R, halo, SH, SR, NH₂, NHR, NR₂, or CN, wherein R is an alkyl moiety. Nucleotide analogs are also meant to include nucleotides with bases such as inosine, queuosine, xanthine, sugars such as 2′-methyl ribose, non-natural phosphodiester linkages such as methylphosphonates, phosphorothioates and peptides.

Modified bases refer to nucleotide bases such as, for example, adenine, guanine, cytosine, thymine, uracil, xanthine, inosine, and queuosine that have been modified by the replacement or addition of one or more atoms or groups. Some examples of types of modifications that can comprise nucleotides that are modified with respect to the base moieties include but are not limited to, alkylated, halogenated, thiolated, aminated, amidated, or acetylated bases, individually or in combination. More specific examples include, for example, 5-propynyluridine, 5-propynylcytidine, 6-methyladenine, 6-methylguanine, N,N,-dimethyladenine, 2-propyladenine, 2-propylguanine, 2-aminoadenine, 1-methylinosine, 3-methyluridine, 5-methylcytidine, 5-methyluridine and other nucleotides having a modification at the 5 position, 5-(2-amino)propyl uridine, 5-halocytidine, 5-halouridine, 4-acetylcytidine, 1-methyladenosine, 2-methyladenosine, 3-methylcytidine, 6-methyluridine, 2-methylguanosine, 7-methylguanosine, 2,2-dimethylguanosine, 5-methylaminoethyluridine, 5-methyloxyuridine, deazanucleotides such as 7-deaza-adenosine, 6-azouridine, 6-azocytidine, 6-azothymidine, 5-methyl-2-thiouridine, other thio bases such as 2-thiouridine and 4-thiouridine and 2-thiocytidine, dihydrouridine, pseudouridine, queuosine, archaeosine, naphthyl and substituted naphthyl groups, any O- and N-alkylated purines and pyrimidines such as N6-methyladenosine, 5-methylcarbonylmethyluridine, uridine 5-oxyacetic acid, pyridine-4-one, pyridine-2-one, phenyl and modified phenyl groups such as aminophenol or 2,4,6-trimethoxy benzene, modified cytosines that act as G-clamp nucleotides, 8-substituted adenines and guanines, 5-substituted uracils and thymines, azapyrimidines, carboxyhydroxyalkyl nucleotides, carboxyalkylaminoalkyl nucleotides, and alkylcarbonylalkylated nucleotides. Modified nucleotides also include those nucleotides that are modified with respect to the sugar moiety, as well as nucleotides having sugars or analogs thereof that are not ribosyl. For example, the sugar moieties may be, or be based on, mannoses, arabinoses, glucopyranoses, galactopyranoses, 4′-thioribose, and other sugars, heterocycles, or carbocycles.

The term nucleotide is also meant to include what are known in the art as universal bases. By way of example, universal bases include but are not limited to 3-nitropyrrole, 5-nitroindole, or nebularine. The term “nucleotide” is also meant to include the N3′ to P5′ phosphoramidate, resulting from the substitution of a ribosyl 3′ oxygen with an amine group.

Further, the term nucleotide also includes those species that have a detectable label, such as for example a radioactive or fluorescent moiety, or mass label attached to the nucleotide.

Polynucleotide

The term “polynucleotide” refers to polymers of nucleotides, and includes but is not limited to DNA, RNA, DNA/RNA hybrids including polynucleotide chains of regularly and/or irregularly alternating deoxyribosyl moieties and ribosyl moieties (i.e., wherein alternate nucleotide units have an —OH, then and —H, then an —OH, then an —H, and so on at the 2′ position of a sugar moiety), and modifications of these kinds of polynucleotides, wherein the attachment of various entities or moieties to the nucleotide units at any position are included.

Polyribonucleotide

The term “polyribonucleotide” refers to a polynucleotide comprising two or more modified or unmodified ribonucleotides and/or their analogs. The term “polyribonucleotide” is used interchangeably with the term “oligoribonucleotide.”

Ribonucleotide and Ribonucleic Acid

The term “ribonucleotide” and the phrase “ribonucleic acid” (RNA), refer to a modified or unmodified nucleotide or polynucleotide comprising at least one ribonucleotide unit. A ribonucleotide unit comprises an hydroxyl group attached to the 2′ position of a ribosyl moiety that has a nitrogenous base attached in N-glycosidic linkage at the 1′ position of a ribosyl moiety, and a moiety that either allows for linkage to another nucleotide or precludes linkage.

DETAILED DESCRIPTION OF THE INVENTION

The present invention is directed to improving the efficiency of gene silencing by siRNA. Through the inclusion of multiple siRNA sequences that are targeted to a particular gene and/or selecting an siRNA sequence based on certain defined criteria, improved efficiency may be achieved.

The present invention will now be described in connection with preferred embodiments. These embodiments are presented in order to aid in an understanding of the present invention and are not intended, and should not be construed, to limit the invention in any way. All alternatives, modifications and equivalents that may become apparent to those of ordinary skill upon reading this disclosure are included within the spirit and scope of the present invention.

Furthermore, this disclosure is not a primer on RNA interference. Basic concepts known to persons skilled in the art have not been set forth in detail.

The present invention is directed to increasing the efficiency of RNAi, particularly in mammalian systems. Accordingly, the present invention provides kits, siRNAs and methods for increasing siRNA efficacy.

According to a first embodiment, the present invention provides a kit for gene silencing, wherein said kit is comprised of a pool of at least two siRNA duplexes, each of which is comprised of a sequence that is complementary to a portion of the sequence of one or more target messenger RNA, and each of which is selected using non-target specific criteria. Each of the at least two siRNA duplexes of the kit complementary to a portion of the sequence of one or more target mRNAs is preferably selected using Formula X.

According to a second embodiment, the present invention provides a method for selecting an siRNA, said method comprising applying selection criteria to a set of potential siRNA that comprise 18-30 base pairs, wherein said selection criteria are non-target specific criteria, and said set comprises at least two siRNAs and each of said at least two siRNAs contains a sequence that is at least substantially complementary to a target gene; and determining the relative functionality of the at least two siRNAs.

In one embodiment, the present invention also provides a method wherein said selection criteria are embodied in a formula comprising: (−14)*G₁₃−13*A₁−12*U₇−11*U₂−10*A₁₁−10*U₄−10*C₃−10*C₅−10*C₆−9*A₁₀−9*U₉−9*C₁₈−8*G₁₀−7*U₁−7*U₁₆−7*C₁₇−7*C₁₉+7*U₁₇+8*A₂+8*A₄+8*A₅+8*C₄+9*G₈+10*A₇+10*U₁₈+11*A₁₉+11*C₉+15*G₁+18*A₃+19*U₁₀−Tm−3* (GC_(total))−6*(GC₁₅₋₁₉)−30*X; or   Formula VIII (−8)*A1+(−1)*A2+(12)*A3+(7)*A4+(18)*A5+(12)*A6+(19)*A7+(6)*A8+(−4)*A9+(−5)*A10+(−2)*A11+(−5)*A12+(17)*A13+(−3)*A14+(4)*A15+(2)*A16+(8)*A17+(11)*A18+(30)*A19+(−13)*U1+(−10)*U2+(2)*U3+(−2)*U4+(−5)*U5+(5)*U6+(−2)*U7+(−10)*U8+(−5)*U9+(15)*U10+(−1)*U11+(0)*U12+(10)*U13+(−9)*U14+(−13)*U15+(−10)*U16+(3)*U17+(9)*U18+(9)*U19+(7)*C1+(3)*C2+(−21)*C3+(5)*C4+(−9)*C5+(−20)*C6+(−18)*C7+(−5)*C8+(5)*C9+(1)*C10+(2)*C11+(−5)*C12+(−3)*C13+(−6)*C14+(−2)*C15+(−5)*C16+(−3)*C17+(−12)*C18+(−18)*C19+(14)*G1+(8)*G2+(7)*G3+(−10)*G4+(−4)*G5+(2)*G6+(1)*G7+(9)*G8+(5)*G9+(−11)*G10+(1)*G11+(9)*G12+(−24)*G13+(18)*G14+(11)*G15+(13)*G16+(−7)*G17+(−9)*G18+(−22)*G19+6*(number of A+U in position 15-19)−3*(number of G+C in whole siRNA),   Formula X wherein position numbering begins at the 5′-most position of a sense strand, and

-   -   A₁=1 if A is the base at position 1 of the sense strand,         otherwise its value is 0;     -   A₂=1 if A is the base at position 2 of the sense strand,         otherwise its value is 0;     -   A₃=1 if A is the base at position 3 of the sense strand,         otherwise its value is 0;     -   A₄=1 if A is the base at position 4 of the sense strand,         otherwise its value is 0;     -   A₅=1 if A is the base at position 5 of the sense strand,         otherwise its value is 0;     -   A₆=1 if A is the base at position 6 of the sense strand,         otherwise its value is 0;     -   A₇=1 if A is the base at position 7 of the sense strand,         otherwise its value is 0;     -   A₁₀=1 if A is the base at position 10 of the sense strand,         otherwise its value is 0;     -   A₁₁=1 if A is the base at position 11 of the sense strand,         otherwise its value is 0;     -   A₁₃=1 if A is the base at position 13 of the sense strand,         otherwise its value is 0;     -   A₁₉=1 if A is the base at position 19 of the sense strand,         otherwise if another base is present or the sense strand is only         18 base pairs in length, its value is 0;     -   C₃=1 if C is the base at position 3 of the sense strand,         otherwise its value is 0;     -   C₄=1 if C is the base at position 4 of the sense strand,         otherwise its value is 0;     -   C₅=1 if C is the base at position 5 of the sense strand,         otherwise its value is 0;     -   C₆=1 if C is the base at position 6 of the sense strand,         otherwise its value is 0;     -   C₇=1 if C is the base at position 7 of the sense strand,         otherwise its value is 0;     -   C₉=1 if C is the base at position 9 of the sense strand,         otherwise its value is 0;     -   C₁₇=1 if C is the base at position 17 of the sense strand,         otherwise its value is 0;     -   C₁₈=1 if C is the base at position 18 of the sense strand,         otherwise its value is 0;     -   C₁₉=1 if C is the base at position 19 of the sense strand,         otherwise if another base is present or the sense strand is only         18 base pairs in length, its value is 0;     -   G₁=1 if G is the base at position 1 on the sense strand,         otherwise its value is 0;     -   G₂=1 if G is the base at position 2 of the sense strand,         otherwise its value is 0;     -   G₈=1 if G is the base at position 8 on the sense strand,         otherwise its value is 0;     -   G₁₀=1 if G is the base at position 10 on the sense strand,         otherwise its value is 0;     -   G₁₃=1 if G is the base at position 13 on the sense strand,         otherwise its value is 0;     -   G₁₉=1 if G is the base at position 19 of the sense strand,         otherwise if another base is present or the sense strand is only         18 base pairs in length, its value is 0;     -   U₁=1 if U is the base at position 1 on the sense strand,         otherwise its value is 0;     -   U₂=1 if U is the base at position 2 on the sense strand,         otherwise its value is 0;     -   U₃=1 if U is the base at position 3 on the sense strand,         otherwise its value is 0;     -   U₄=1 if U is the base at position 4 on the sense strand,         otherwise its value is 0;     -   U₇=1 if U is the base at position 7 on the sense strand,         otherwise its value is 0;     -   U₉=1 if U is the base at position 9 on the sense strand,         otherwise its value is 0;     -   U ₁₀=1 if U is the base at position 10 on the sense strand,         otherwise its value is 0;     -   U₁₅=1 if U is the base at position 15 on the sense strand,         otherwise its value is 0;     -   U₁₆=1 if U is the base at position 16 on the sense strand,         otherwise its value is 0;     -   U₁₇=1 if U is the base at position 17 on the sense strand,         otherwise its value is 0;     -   U₁₈=1 if U is the base at position 18 on the sense strand,         otherwise its value is 0.     -   GC₁₅₋₁₉=the number of G and C bases within positions 15-19 of         the sense strand, or within positions 15-18 if the sense strand         is only 18 base pairs in length;     -   GC_(total)=the number of G and C bases in the sense strand;     -   Tm=100 if the siRNA oligo has the internal repeat longer then 4         base pairs, otherwise its value is 0; and     -   X=the number of times that the same nucleotide repeats four or         more times in a row.

Any of the methods of selecting siRNA in accordance with the invention can further comprise comparing the internal stability profiles of the siRNAs to be selected, and selecting those siRNAs with the most favorable internal stability profiles. Any of the methods of selecting siRNA can further comprise selecting either for or against sequences that contain motifs that induce cellular stress. Such motifs include, for example, toxicity motifs. Any of the methods of selecting siRNA can further comprise either selecting for or selecting against sequences that comprise stability motifs.

In another embodiment, the present invention provides a method of gene silencing, comprising introducing into a cell at least one siRNA selected according to any of the methods of the present invention. The siRNA can be introduced by allowing passive uptake of siRNA, or through the use of a vector.

According to a third embodiment, the invention provides a method for developing an algorithm for selecting siRNA, said method comprising: (a) selecting a set of siRNA; (b) measuring gene silencing ability of each siRNA from said set; (c) determining relative functionality of each siRNA; (d) determining improved functionality by the presence or absence of at least one variable selected from the group consisting of the presence or absence of a particular nucleotide at a particular position, the total number of As and Us in positions 15-19, the number of times that the same nucleotide repeats within a given sequence, and the total number of Gs and Cs; and (e) developing an algorithm using the information of step (d).

In another embodiment, the invention provides a method for selecting an siRNA with improved functionality, comprising using the above-mentioned algorithm to identify an siRNA of improved functionality.

According to a fourth embodiment, the present invention provides a kit, wherein said kit is comprised of at least two siRNAs, wherein said at least two siRNAs comprise a first optimized siRNA and a second optimized siRNA, wherein said first optimized siRNA and said second optimized siRNA are optimized according a formula comprising Formula X.

According to a fifth embodiment, the present invention provides a method for identifying a hyperfunctional siRNA, comprising applying selection criteria to a set of potential siRNA that comprise 18-30 base pairs, wherein said selection criteria are non-target specific criteria, and said set comprises at least two siRNAs and each of said at least two siRNAs contains a sequence that is at least substantially complementary to a target gene; determining the relative functionality of the at least two siRNAs and assigning each of the at least two siRNAs a functionality score; and selecting siRNAs from the at least two siRNAs that have a functionality score that reflects greater than 80 percent silencing at a concentration in the picomolar range, wherein said greater than 80 percent silencing endures for greater than 120 hours.

In other embodiments, the invention provides kits and/or methods wherein the siRNA are comprised of two separate polynucleotide strands; wherein the siRNA are comprised of a single contiguous molecule such as, for example, a unimolecular siRNA (comprising, for example, either a nucleotide or non-nucleotide loop); wherein the siRNA are expressed from one or more vectors; and wherein two or more genes are silenced by a single administration of siRNA.

According to a sixth embodiment, the present invention provides a hyperfunctional siRNA that is capable of silencing Bc12.

According to a seventh embodiment, the present invention provides a method for developing an siRNA algorithm for selecting functional and hyperfunctional siRNAs for a given sequence. The method comprises:

-   -   (a) selecting a set of siRNAs;     -   (b) measuring the gene silencing ability of each siRNA from said         set;     -   (c) determining the relative functionality of each siRNA;     -   (d) determining the amount of improved functionality by the         presence or absence of at least one variable selected from the         group consisting of the total GC content, melting temperature of         the siRNA, GC content at positions 15-19, the presence or         absence of a particular nucleotide at a particular position,         relative thermodynamic stability at particular positions in a         duplex, and the number of times that the same nucleotide repeats         within a given sequence; and     -   (e) developing an algorithm using the information of step (d).         According to this embodiment, preferably the set of siRNAs         comprises at least 90 siRNAs from at least one gene, more         preferably at least 180 siRNAs from at least two different         genes, and most preferably at least 270 and 360 siRNAs from at         least three and four different genes, respectively.         Additionally, in step (d) the determination is made with         preferably at least two, more preferably at least three, even         more preferably at least four, and most preferably all of the         variables. The resulting algorithm is not target sequence         specific.

In another embodiment, the present invention provides rationally designed siRNAs identified using the formulas above.

In yet another embodiment, the present invention is directed to hyperfunctional siRNA.

The ability to use the above algorithms, which are not sequence or species specific, allows for the cost-effective selection of optimized siRNAs for specific target sequences. Accordingly, there will be both greater efficiency and reliability in the use of siRNA technologies.

The methods disclosed herein can be used in conjunction with comparing internal stability profiles of selected siRNAs, and designing an siRNA with a desireable internal stability profile; and/or in conjunction with a selection either for or against sequences that contain motifs that induce cellular stress, for example, cellular toxicity.

Any of the methods disclosed herein can be used to silence one or more genes by introducing an siRNA selected, or designed, in accordance with any of the methods disclosed herein. The siRNA(s) can be introduced into the cell by any method known in the art, including passive uptake or through the use of one or more vectors.

Any of the methods and kits disclosed herein can employ either unimolecular siRNAs, siRNAs comprised of two separate polynucleotide strands, or combinations thereof. Any of the methods disclosed herein can be used in gene silencing, where two or more genes are silenced by a single administration of siRNA(s). The siRNA(s) can be directed against two or more target genes, and administered in a single dose or single transfection, as the case may be.

Optimizing siRNA

According to one embodiment, the present invention provides a method for improving the effectiveness of gene silencing for use to silence a particular gene through the selection of an optimal siRNA. An siRNA selected according to this method may be used individually, or in conjunction with the first embodiment, i.e., with one or more other siRNAs, each of which may or may not be selected by this criteria in order to maximize their efficiency.

The degree to which it is possible to select an siRNA for a given mRNA that maximizes these criteria will depend on the sequence of the mRNA itself. However, the selection criteria will be independent of the target sequence. According to this method, an siRNA is selected for a given gene by using a rational design. That said, rational design can be described in a variety of ways. Rational design is, in simplest terms, the application of a proven set of criteria that enhance the probability of identifying a functional or hyperfunctional siRNA. In one method, rationally designed siRNA can be identified by maximizing one or more of the following criteria:

-   -   1. A low GC content, preferably between about 30-52%.     -   2. At least 2, preferably at least 3 A or U bases at positions         15-19 of the siRNA on the sense strand.     -   3. An A base at position 19 of the sense strand.     -   4. An A base at position 3 of the sense strand.     -   5. A U base at position 10 of the sense strand.     -   6. An A base at position 14 of the sense strand.     -   7. A base other than C at position 19 of the sense strand.     -   8. A base other than G at position 13 of the sense strand.     -   9. A Tm, which refers to the character of the internal repeat         that results in inter- or intramolecular structures for one         strand of the duplex, that is preferably not stable at greater         than 50° C., more preferably not stable at greater than 37° C.,         even more preferably not stable at greater than 30° C. and most         preferably not stable at greater than 20° C.     -   10. A base other than U at position 5 of the sense strand.     -   11. A base other than A at position 11 of the sense strand.     -   12. A base other than an A at position 1 of the sense strand.     -   13. A base other than an A at position 2 of the sense strand.     -   14. An A base at position 4 of the sense strand.     -   15. An A base at position 5 of the sense strand.     -   16. An A base at position 6 of the sense strand.     -   17. An A base at position 7 of the sense strand.     -   18. An A base at position 8 of the sense strand.     -   19. A base other than an A at position 9 of the sense strand.     -   20. A base other than an A at position 10 of the sense strand.     -   21. A base other than an A at position 11 of the sense strand.     -   22. A base other than an A at position 12 of the sense strand.     -   23. An A base at position 13 of the sense strand.     -   24. A base other than an A at position 14 of the sense strand.     -   25. An A base at position 15 of the sense strand     -   26. An A base at position 16 of the sense strand.     -   27. An A base at position 17 of the sense strand.     -   28. An A base at position 18 of the sense strand.     -   29. A base other than a U at position 1 of the sense strand.     -   30. A base other than a U at position 2 of the sense strand.     -   31. A U base at position 3 of the sense strand.     -   32. A base other than a U at position 4 of the sense strand.     -   33. A base other than a U at position 5 of the sense strand.     -   34. A U base at position 6 of the sense strand.     -   35. A base other than a U at position 7 of the sense strand.     -   36. A base other than a U at position 8 of the sense strand.     -   37. A base other than a U at position 9 of the sense strand.     -   38. A base other than a U at position 11 of the sense strand.     -   39. A U base at position 13 of the sense strand.     -   40. A base other than a U at position 14 of the sense strand.     -   41. A base other than a U at position 15 of the sense strand.     -   42. A base other than a U at position 16 of the sense strand.     -   43. A U base at position 17 of the sense strand.     -   44. A U base at position 18 of the sense strand.     -   45. A U base at position 19 of the sense strand.     -   46. A C base at position 1 of the sense strand.     -   47. A C base at position 2 of the sense strand.     -   48. A base other than a C at position 3 of the sense strand.     -   49. A C base at position 4 of the sense strand.     -   50. A base other than a C at position 5 of the sense strand.     -   51. A base other than a C at position 6 of the sense strand.     -   52. A base other than a C at position 7 of the sense strand.     -   53. A base other than a C at position 8 of the sense strand.     -   54. A C base at position 9 of the sense strand.     -   55. A C base at position 10 of the sense strand.     -   56. A C base at position 11 of the sense strand.     -   57. A base other than a C at position 12 of the sense strand.     -   58. A base other than a C at position 13 of the sense strand.     -   59. A base other than a C at position 14 of the sense strand.     -   60. A base other than a C at position 15 of the sense strand.     -   61. A base other than a C at position 16 of the sense strand.     -   62. A base other than a C at position 17 of the sense strand.     -   63. A base other than a C at position 18 of the sense strand.     -   64. A G base at position 1 of the sense strand.     -   65. A G base at position 2 of the sense strand.     -   66. A G base at position 3 of the sense strand.     -   67. A base other than a G at position 4 of the sense strand.     -   68. A base other than a G at position 5 of the sense strand.     -   69. A G base at position 6 of the sense strand.     -   70. A G base at position 7 of the sense strand.     -   71. A G base at position 8 of the sense strand.     -   72. A G base at position 9 of the sense strand.     -   73. A base other than a G at position 10 of the sense strand.     -   74. A G base at position 11 of the sense strand.     -   75. A G base at position 12 of the sense strand.     -   76. A G base at position 14 of the sense strand.     -   77. A G base at position 15 of the sense strand.     -   78. A G base at position 16 of the sense strand.     -   79. A base other than a G at position 17 of the sense strand.     -   80. A base other than a G at position 18 of the sense strand.     -   81. A base other than a G at position 19 of the sense strand.

The importance of various criteria can vary greatly. For instance, a C base at position 10 of the sense strand makes a minor contribution to duplex functionality. In contrast, the absence of a C at position 3 of the sense strand is very important. Accordingly, preferably an siRNA will satisfy as many of the aforementioned criteria as possible.

With respect to the criteria, GC content, as well as a high number of AU in positions 15-19 of the sense strand, may be important for easement of the unwinding of double stranded siRNA duplex. Duplex unwinding has been shown to be crucial for siRNA functionality in vivo.

With respect to criterion 9, the internal structure is measured in terms of the melting temperature of the single strand of siRNA, which is the temperature at which 50% of the molecules will become denatured. With respect to criteria 2-8 and 10-11, the positions refer to sequence positions on the sense strand, which is the strand that is identical to the mRNA.

In one preferred embodiment, at least criteria 1 and 8 are satisfied. In another preferred embodiment, at least criteria 7 and 8 are satisfied. In still another preferred embodiment, at least criteria 1, 8 and 9 are satisfied.

It should be noted that all of the aforementioned criteria regarding sequence position specifics are with respect to the 5′ end of the sense strand. Reference is made to the sense strand, because most databases contain information that describes the information of the mRNA. Because according to the present invention a chain can be from 18 to 30 bases in length, and the aforementioned criteria assumes a chain 19 base pairs in length, it is important to keep the aforementioned criteria applicable to the correct bases.

When there are only 18 bases, the base pair that is not present is the base pair that is located at the 3′ of the sense strand. When there are twenty to thirty bases present, then additional bases are added at the 5′ end of the sense chain and occupy positions ⁻1 to ⁻11. Accordingly, with respect to SEQ. ID NO. 0001 NNANANNNNUCNAANNNNA and SEQ. ID NO. 0028 GUCNNANANNNNUCNAANNNNA, both would have A at position 3, A at position 5, U at position 10, C at position 11, A and position 13, A and position 14 and A at position 19. However, SEQ. ID NO. 0028 would also have C at position −1, U at position −2 and G at position −3.

For a 19 base pair siRNA, an optimal sequence of one of the strands may be represented below, where N is any base, A, C, G, or U: NNANANNNNUCNAANNNNA. SEQ. ID NO. 0001 NNANANNNNUGNAANNNNA. SEQ. ID NO. 0001 NNANANNNNUUNAANNNNA. SEQ. ID NO. 0002 NNANANNNNUCNCANNNNA. SEQ. ID NO. 0003 NNANANNNNUGNCANNNNA. SEQ. ID NO. 0004 NNANANNNNUUNCANNNNA. SEQ. ID NO. 0005 NNANANNNNUCNUANNNNA. SEQ. ID NO. 0006 NNANANNNNUGNUANNNNA. SEQ. ID NO. 0007 NNANANNNNUUNUANNNNA. SEQ. ID NO. 0008 NNANCNNNNUCNAANNNNA. SEQ. ID NO. 0010 NNANCNNNNUGNAANNNNA. SEQ. ID NO. 0011 NNANCNNNNUUNAANNNNA. SEQ. ID NO. 0012 NNANCNNNNUCNCANNNNA. SEQ. ID NO. 0013 NNANCNNNNUGNCANNNNA. SEQ. ID NO. 0014 NNANCNNNNUUNCANNNNA. SEQ. ID NO. 0015 NANCNNNNUCNUANNNNA. SEQ. ID NO. 0016 NNANCNNNNUGNUANNNNA. SEQ. ID NO. 0017 NNANCNNNNUUNUANNNNA. SEQ. ID NO. 0018 NNANGNNNNUCNAANNNNA. SEQ. ID NO. 0019 NNANGNNNNUGNAANNNNA. SEQ. ID NO. 0020 NNANGNNNNUUNAANNNNA. SEQ. ID NO. 0021 NNANGNNNNUCNCANNNNA. SEQ. ID NO. 0022 NNANGNNNNUGNCANNNNA. SEQ. ID NO. 0023 NNANGNNNNUUNCANNNNA. SEQ. ID NO. 0024 NNANGNNNNUCNUANNNNA. SEQ. ID NO. 0025 NNANGNNNNUGNUANNNNA. SEQ. ID NO. 0026 NNANGNNNNNUNUANNNNA. SEQ. ID NO. 0027

In one embodiment, the sequence used as an siRNA is selected by choosing the siRNA that score highest according to one of the following seven algorithms that are represented by Formulas I-VII: Relative functionality of siRNA=−(GC/3)+(AU ₁₅₋₁₉)−Tm_(20°C.))*3−(G ₁₃)*3)−(C ₁₉)   Formula I Relative functionality of siRNA=−(GC/3)−(AU ₁₅₋₁₉)*3−(G ₁₃)*3−(C ₁₉)+(A ₁₉)*2+(A ₃)   Formula II Relative functionality of siRNA=−(GC/3)+(AU ₁₅₋₁₉)−(Tm_(20°C.))*3   Formula III Relative functionality of siRNA=GC/2+(AU ₁₅₋₁₉)/2−(Tm_(20°C.))*2−(G ₁₃)*3−(C₁₉)+(A ₁₉)*2+(A ₃)+(U ₁₀)+(A ₁₄)−(U ₅)−(A ₁₁)   Formula IV Relative functionality of siRNA=−(G ₁₃)*3−(C ₁₉)+(A ₁₉)*2+(A ₃)+(U ₁₀)+(A ₁₄)−(U ₅)−(A ₁₁)   Formula V Relative functionality of siRNA=−(G ₁₃)*3−(C ₁₉)+(A ₁₉)*2+(A ₃)   Formula VI Relative functionality of siRNA=−(GC/2)+(AU ₁₅₋₁₉)/2−(Tm_(20°C.))*1−(G ₁₃)*3−(C ₁₉)+(A ₁₉)*3+(A ₃)*3+(U ₁₀)/2+(A ₁₄)/2−(U ₅)/2−(A ₁₁)/2   Formula VII In Formulas I-VII:

-   -   wherein A₁₉=1 if A is the base at position 19 on the sense         strand, otherwise its value is 0,         -   AU₁₅₋₁₉=0-5 depending on the number of A or U bases on the             sense strand at positions 15-19;         -   G₁₃=1 if G is the base at position 13 on the sense strand,             otherwise its value is 0;         -   C₁₉=1 if C is the base at position 19 of the sense strand,             otherwise its value is 0;         -   GC=the number of G and C bases in the entire sense strand;         -   Tm_(20° C.)=1 if the Tm is greater than 20° C.;         -   A₃=1 if A is the base at position 3 on the sense strand,             otherwise its value is 0;         -   U₁₀=1 if U is the base at position 10 on the sense strand,             otherwise its value is 0;         -   A₁₄=1 if A is the base at position 14 on the sense strand,             otherwise its value is 0;         -   U₅=1 if U is the base at position 5 on the sense strand,             otherwise its value is 0; and         -   A₁₁=1 if A is the base at position 11 of the sense strand,             otherwise its value is 0.

Formulas I-VII provide relative information regarding functionality. When the values for two sequences are compared for a given formula, the relative functionality is ascertained; a higher positive number indicates a greater functionality. For example, in many applications a value of 5 or greater is beneficial.

Additionally, in many applications, more than one of these formulas would provide useful information as to the relative functionality of potential siRNA sequences. However, it is beneficial to have more than one type of formula, because not every formula will be able to help to differentiate among potential siRNA sequences. For example, in particularly high GC mRNAs, formulas that take that parameter into account would not be useful and application of formulas that lack GC elements (e.g., formulas V and VI) might provide greater insights into duplex functionality. Similarly, formula II might by used in situations where hairpin structures are not observed in duplexes, and formula IV might be applicable for sequences that have higher AU content. Thus, one may consider a particular sequence in light of more than one or even all of these algorithms to obtain the best differentiation among sequences. In some instances, application of a given algorithim may identify an unususally large number of potential siRNA sequences, and in those cases, it may be appropriate to re-analyze that sequence with a second algorithm that is, for instance, more stringent. Alternatively, it is conceivable that analysis of a sequence with a given formula yields no acceptable siRNA sequences (i.e., low SMARTscores™). In this instance, it may be appropriate to re-analyze that sequences with a second algorithm that is, for instance, less stringent. In still other instances, analysis of a single sequence with two separate formulas may give rise to conflicting results (i.e., one formula generates a set of siRNA with high SMARTscores™ while the other formula identifies a set of siRNA with low SMARTscores™). In these instances, it may be necessary to determine which weighted factor(s) (e.g., GC content) are contributing to the discrepancy and assessing the sequence to decide whether these factors should or should not be included. Alternatively, the sequence could be analyzed by a third, fourth, or fifth algorithm to identify a set of rationally designed siRNA.

The above-referenced criteria are particularly advantageous when used in combination with pooling techniques as depicted in Table I: TABLE I Functional Probability Oligos Pools Criteria >95% >80% <70% >95% >80% <70% Current 33.0 50.0 23.0 79.5 97.3 0.3 New 50.0 88.5 8.0 93.8 99.98 0.005 (GC) 28.0 58.9 36.0 72.8 97.1 1.6 The term “current” used in Table I refers to Tuschl's conventional siRNA parameters (Elbashir, S. M. et al. (2002) “Analysis of gene function in somatic mammalian cells using small interfering RNAs” Methods 26: 199-213). “New” refers to the design parameters described in Formulas I-VII. “GC” refers to criteria that select siRNA solely on the basis of GC content.

As Table I indicates, when more functional siRNA duplexes are chosen, siRNAs that produce <70% silencing drops from 23% to 8% and the number of siRNA duplexes that produce >80% silencing rises from 50% to 88.5%. Further, of the siRNA duplexes with >80% silencing, a larger portion of these siRNAs actually silence >95% of the target expression (the new criteria increases the portion from 33% to 50%). Using this new criteria in pooled siRNAs, shows that, with pooling, the amount of silencing >95% increases from 79.5% to 93.8% and essentially eliminates any siRNA pool from silencing less than 70%.

Table II similarly shows the particularly beneficial results of pooling in combination with the aforementioned criteria. However, Table II, which takes into account each of the aforementioned variables, demonstrates even a greater degree of improvement in functionality. TABLE II Functional Probability Oligos Pools Func- Non- Func- Non- tional Average functional tional Average functional Random 20 40 50 67 97 3 Criteria 1 52 99 0.1 97 93 0.0040 Criteria 4 89 99 0.1 99 99 0.0000 The terms “functional,” “Average,” and “Non-functional” used in Table II, refer to siRNA that exhibit >80%, >50%, and <50% functionality, respectively. Criteria 1 and 4 refer to specific criteria described above.

The above-described algorithms may be used with or without a computer program that allows for the inputting of the sequence of the mRNA and automatically outputs the optimal siRNA. The computer program may, for example, be accessible from a local terminal or personal computer, over an internal network or over the Internet.

In addition to the formulas above, more detailed algorithms may be used for selecting siRNA. Preferably, at least one RNA duplex of 18-30 base pairs is selected such that it is optimized according a formula selected from: (−14)*G₁₃−13*A₁−12*U₇−11*U₂−10*A₁₁−10*U₄−10*C₃−10*C₅−10*C₆−9*A₁₀−9*U₉−9*C₁₈−8*G₁₀−7*U₁−7*U₁₆−7*C₁₇−7*C₁₉+7*U₁₇+8*A₂+8*A₄+8*A₅+8*C₄+9*G₈+10*A₇+10*U₁₈+11*A₁₉+11*C₉+15*G₁+18*A₃+19*U₁₀−Tm−3* (GC_(total))−6*(GC₁₅₋₁₉)−30*X; and   Formula VIII (14.1)*A₃+(14.9)*A₆+(17.6)*A₁₃+(24.7)*A₁₉+(14.2)*U₁₀+((10.5)* C₉+(23.9)*G₁+(16.3)*G₂+(−12.3)*A₁₁+(−19.3)*U₁+(−12.1)*U₂+(−11)*U₃+(−15.2)*U₁₅+(−11.3)*U₁₆+(−11.8)*C₃+(−17.4)*C₆+(−10.5)*C₇+(−13.7)*G₁₃+(−25.9)*G₁₉−Tm−3*(GC_(total))−6*(GC₁₅₋₁₉)−30*X; and   Formula IX (−8)*A1+(−1)*A2+(12)*A3+(7)*A4+(18)*A5+(12)*A6+(19)*A7+(6)*A8+(−4)*A9+(−5)*A10+(−2)*A11+(−5)*A12+(17)*A13+(−3)*A14+(4)*A15+(2)*A16+(8)*A17+(11)*A18+(30)*A19+(−13)*U1+(−10)*U2+(2)*U3+(−2)*U4+(−5)*U5+(5)*U6+(−2)*U7+(−10)*U8+(−5)*U9+(15)*U10+(−1)*U11+(0)*U12+(10)*U13+(−9)*U14+(−13)*U15+(−10)*U16+(3)*U17+(9)*U18+(9)*U19+(7)*C1+(3)*C2+(−21)*C3+(5)*C4+(−9)*C5+(−20)*C6+(−18)*C7+(−5)*C8+(5)*C9+(1)*C10+(2)*C11+(−5)*C12+(−3)*C13+(−6)*C14+(−2)*C15+(−5)*C16+(−3)*C17+(−12)*C18+(−18)*C19+(14)*G1+(8)*G2+(7)*G3+(−10)*G4+(−4)*G5+(2)*G6+(1)*G7+(9)*G8+(5)*G9+(−11)*G10+(1)*G11+(9)*G12+(−24)*G13+(18)*G14+(11)*G15+(13)*G16+(−7)*G17+(−9)*G18+(−22)*G19+6*(number of A+U in position 15-19)−3*(number of G+C in whole siRNA),   Formula X wherein

-   -   A₁=1 if A is the base at position 1 of the sense strand,         otherwise its value is 0;     -   A₂=1 if A is the base at position 2 of the sense strand,         otherwise its value is 0;     -   A₃=1 if A is the base at position 3 of the sense strand,         otherwise its value is 0;     -   A₄=1 if A is the base at position 4 of the sense strand,         otherwise its value is 0;     -   A₅=1 if A is the base at position 5 of the sense strand,         otherwise its value is 0;     -   A₆=1 if A is the base at position 6 of the sense strand,         otherwise its value is 0;     -   A₇=1 if A is the base at position 7 of the sense strand,         otherwise its value is 0;     -   A₁₀=1 if A is the base at position 10 of the sense strand,         otherwise its value is 0;     -   A₁₁=1 if A is the base at position 11 of the sense strand,         otherwise its value is 0;     -   A₁₃=1 if A is the base at position 13 of the sense strand,         otherwise its value is 0;     -   A₁₉=1 if A is the base at position 19 of the sense strand,         otherwise if another base is present or the sense strand is only         18 base pairs in length, its value is 0;     -   C₃=1 if C is the base at position 3 of the sense strand,         otherwise its value is 0;     -   C₄=1 if C is the base at position 4 of the sense strand,         otherwise its value is 0;     -   C₅=1 if C is the base at position 5 of the sense strand,         otherwise its value is 0;     -   C₆=1 if C is the base at position 6 of the sense strand,         otherwise its value is 0;     -   C₇=1 if C is the base at position 7 of the sense strand,         otherwise its value is 0;     -   C₉=1 if C is the base at position 9 of the sense strand,         otherwise its value is 0;     -   C₁₇=1 if C is the base at position 17 of the sense strand,         otherwise its value is 0;     -   C₁₈=1 if C is the base at position 18 of the sense strand,         otherwise its value is 0;     -   C₁₉=1 if C is the base at position 19 of the sense strand,         otherwise if another base is present or the sense strand is only         18 base pairs in length, its value is 0;     -   G₁=1 if G is the base at position 1 on the sense strand,         otherwise its value is 0;     -   G₂=1 if G is the base at position 2 of the sense strand,         otherwise its value is 0;     -   G₈=1 if G is the base at position 8 on the sense strand,         otherwise its value is 0;     -   G₁₀=1 if G is the base at position 10 on the sense strand,         otherwise its value is 0;     -   G₁₃=1 if G is the base at position 13 on the sense strand,         otherwise its value is 0;     -   G₁₉=1 if G is the base at position 19 of the sense strand,         otherwise if another base is present or the sense strand is only         18 base pairs in length, its value is 0;     -   U₁=1 if U is the base at position 1 on the sense strand,         otherwise its value is 0;     -   U₂=1 if U is the base at position 2 on the sense strand,         otherwise its value is 0;     -   U₃=1 if U is the base at position 3 on the sense strand,         otherwise its value is 0;     -   U₄=1 if U is the base at position 4 on the sense strand,         otherwise its value is 0;     -   U₇=1 if U is the base at position 7 on the sense strand,         otherwise its value is 0;     -   U₉=1 if U is the base at position 9 on the sense strand,         otherwise its value is 0;     -   U₁₀=1 if U is the base at position 10 on the sense strand,         otherwise its value is 0;     -   U₁₅=1 if U is the base at position 15 on the sense strand,         otherwise its value is 0;     -   U₁₆=1 if U is the base at position 16 on the sense strand,         otherwise its value is 0;     -   U₁₇=1 if U is the base at position 17 on the sense strand,         otherwise its value is 0;     -   U₁₈=1 if U is the base at position 18 on the sense strand,         otherwise its value is 0;     -   GC₁₅₋₁₉=the number of G and C bases within positions 15-19 of         the sense strand, or within positions 15-18 if the sense strand         is only 18 base pairs in length;     -   GC_(total)=the number of G and C bases in the sense strand;     -   Tm=100 if the siRNA oligo has the internal repeat longer then 4         base pairs, otherwise its value is 0; and     -   X=the number of times that the same nucleotide repeats four or         more times in a row.

The above formulas VIII, IX, and X, as well as formulas I-VII, provide methods for selecting siRNA in order to increase the efficiency of gene silencing. A subset of variables of any of the formulas may be used, though when fewer variables are used, the optimization hierarchy becomes less reliable.

With respect to the variables of the above-referenced formulas, a single letter of A or C or G or U followed by a subscript refers to a binary condition. The binary condition is that either the particular base is present at that particular position (wherein the value is “1”) or the base is not present (wherein the value is “0”). Because position 19 is optional, i.e., there might be only 18 base pairs, when there are only 18 base pairs, any base with a subscript of 19 in the formulas above would have a zero value for that parameter. Before or after each variable is a number followed by *, which indicates that the value of the variable is to be multiplied or weighed by that number.

The numbers preceding the variables A, or G, or C, or U in Formulas VIII, IX, and X (or after the variables in Formula I-VII) were determined by comparing the difference in the frequency of individual bases at different positions in functional siRNA and total siRNA. Specifically, the frequency in which a given base was observed at a particular position in functional groups was compared with the frequency that that same base was observed in the total, randomly selected siRNA set. If the absolute value of the difference between the functional and total values was found to be greater than 6%, that parameter was included in the equation. Thus, for instance, if the frequency of finding a “G” at position 13 (G13) is found to be 6% in a given functional group, and the frequency of G₁₃ in the total population of siRNAs is 20%, the difference between the two values is 6%-20%=−14%. As the absolute value is greater than six (6), this factor (−14) is included in the equation. Thus, in Formula VIII, in cases where the siRNA under study has a G in position 13, the accrued value is (−14)*(1)=−14. In contrast, when a base other than G is found at position 13, the accrued value is (−14)*(0)=0.

When developing a means to optimize siRNAs, the inventors observed that a bias toward low internal thermodynamic stability of the duplex at the 5′-antisense (AS) end is characteristic of naturally occurring miRNA precursors. The inventors extended this observation to siRNAs for which functionality had been assessed in tissue culture.

With respect to the parameter GC₁₅₋₁₉, a value of 0-5 will be ascribed depending on the number of G or C bases at positions 15 to 19. If there are only 18 base pairs, the value is between 0 and 4.

With respect to the criterion GC_(total) content, a number from 0-30 will be ascribed, which correlates to the total number of G and C nucleotides on the sense strand, excluding overhangs. Without wishing to be bound by any one theory, it is postulated that the significance of the GC content (as well as AU content at positions 15-19, which is a parameter for formulas III-VII) relates to the easement of the unwinding of a double-stranded siRNA duplex. Duplex unwinding is believed to be crucial for siRNA functionality in vivo and overall low internal stability, especially low internal stability of the first unwound base pair is believed to be important to maintain sufficient processivity of RISC complex-induced duplex unwinding. If the duplex has 19 base pairs, those at positions 15-19 on the sense strand will unwind first if the molecule exhibits a sufficiently low internal stability at that position. As persons skilled in the art are aware, RISC is a complex of approximately twelve proteins; Dicer is one, but not the only, helicase within this complex. Accordingly, although the GC parameters are believed to relate to activity with Dicer, they are also important for activity with other RISC proteins.

The value of the parameter Tm is 0 when there are no internal repeats longer than (or equal to) four base pairs present in the siRNA duplex; otherwise the value is 1. Thus for example, if the sequence ACGUACGU, or any other four nucleotide (or more) palindrome exists within the structure, the value will be one (1). Alternatively if the structure ACGGACG, or any other 3 nucleotide (or less) palindrome exists, the value will be zero (0).

The variable “X” refers to the number of times that the same nucleotide occurs contiguously in a stretch of four or more units. If there are, for example, four contiguous As in one part of the sequence and elsewhere in the sequence four contiguous Cs, X=2. Further, if there are two separate contiguous stretches of four of the same nucleotides or eight or more of the same nucleotides in a row, then X=2. However, X does not increase for five, six or seven contiguous nucleotides.

Again, when applying Formula VIII, Formula IX, or Formula X, to a given mRNA, (the “target RNA” or “target molecule”), one may use a computer program to evaluate the criteria for every sequence of 18-30 base pairs or only sequences of a fixed length, e.g., 19 base pairs. Preferably the computer program is designed such that it provides a report ranking of all of the potential siRNAs 18-30 base pairs, ranked according to which sequences generate the highest value. A higher value refers to a more efficient siRNA for a particular target gene. The computer program that may be used may be developed in any computer language that is known to be useful for scoring nucleotide sequences, or it may be developed with the assistance of commercially available product such as Microsoft's product.net. Additionally, rather than run every sequence through one and/or another formula, one may compare a subset of the sequences, which may be desirable if for example only a subset are available. For instance, it may be desirable to first perform a BLAST (Basic Local Alignment Search Tool) search and to identify sequences that have no homology to other targets. Alternatively, it may be desirable to scan the sequence and to identify regions of moderate GC context, then perform relevant calculations using one of the above-described formulas on these regions. These calculations can be done manually or with the aid of a computer.

As with Formulas I-VII, either Formula VIII, Formula IX, or Formula X may be used for a given mRNA target sequence. However, it is possible that according to one or the other formula more than one siRNA will have the same value. Accordingly, it is beneficial to have a second formula by which to differentiate sequences. Formulas IX and X were derived in a similar fashion as Formula VIII, yet used a larger data set and thus yields sequences with higher statistical correlations to highly functional duplexes. The sequence that has the highest value ascribed to it may be referred to as a “first optimized duplex.” The sequence that has the second highest value ascribed to it may be referred to as a “second optimized duplex.” Similarly, the sequences that have the third and fourth highest values ascribed to them may be referred to as a third optimized duplex and a fourth optimized duplex, respectively. When more than one sequence has the same value, each of them may, for example, be referred to as first optimized duplex sequences or co-first optimized duplexes. Formula X is similar to Formula IX, yet uses a greater numbers of variables and for that reason, identifies sequences on the basis of slightly different criteria.

It should also be noted that the output of a particular algorithm will depend on several of variables including: (1) the size of the data base(s) being analyzed by the algorithm, and (2) the number and stringency of the parameters being applied to screen each sequence. Thus, for example, in U.S. patent application Ser. No. 10/714,333, entitled “Functional and Hyperfunctional siRNA,” filed Nov. 14, 2003, Formula VIII was applied to the known human genome (ncbi refseq database) through Entrez (efetch). As a result of these procedures, roughly 1.6 million siRNA sequences were identified. Application of Formula VIII to the same database in March of 2004 yielded roughly 2.2 million sequences, a difference of approximately 600,000 sequences resulting from the growth of the database over the course of the months that span this period of time. Application of other formulas (e.g., Formula X) that change the emphasis of, include, or eliminate different variables can yield unequal numbers of siRNAs. Alternatively, in cases where application of one formula to one or more genes fails to yield sufficient numbers of siRNAs with scores that would be indicative of strong silencing, said genes can be reassessed with a second algorithm that is, for instance, less stringent.

siRNA sequences identified using Formula VIII and Formula X (minus sequences generated by Formula VIII) are contained within the enclosed compact disks. The data included on the enclosed compact disks is described more fully below. The sequences identified by Formula VIII and Formula X that are disclosed in the compacts disks may be used in gene silencing applications.

It should be noted that for Formulas VIII, IX, and X all of the aforementioned criteria are identified as positions on the sense strand when oriented in the 5′ to 3′ direction as they are identified in connection with Formulas I-VII unless otherwise specified.

Formulas I-X, may be used to select or to evaluate one, or more than one, siRNA in order to optimize silencing. Preferably, at least two optimized siRNAs that have been selected according to at least one of these formulas are used to silence a gene, more preferably at least three and most preferably at least four. The siRNAs may be used individually or together in a pool or kit. Further, they may be applied to a cell simultaneously or separately. Preferably, the at least two siRNAs are applied simultaneously. Pools are particularly beneficial for many research applications. However, for therapeutics, it may be more desirable to employ a single hyperfunctional siRNA as described elsewhere in this application.

When planning to conduct gene silencing, and it is necessary to choose between two or more siRNAs, one should do so by comparing the relative values when the siRNA are subjected to one of the formulas above. In general a higher scored siRNA should be used.

Useful applications include, but are not limited to, target validation, gene functional analysis, research and drug discovery, gene therapy and therapeutics. Methods for using siRNA in these applications are well known to persons of skill in the art.

Because the ability of siRNA to function is dependent on the sequence of the RNA and not the species into which it is introduced, the present invention is applicable across a broad range of species, including but not limited to all mammalian species, such as humans, dogs, horses, cats, cows, mice, hamsters, chimpanzees and gorillas, as well as other species and organisms such as bacteria, viruses, insects, plants and C. elegans.

The present invention is also applicable for use for silencing a broad range of genes, including but not limited to the roughly 45,000 genes of a human genome, and has particular relevance in cases where those genes are associated with diseases such as diabetes, Alzheimer's, cancer, as well as all genes in the genomes of the aforementioned organisms.

The siRNA selected according to the aforementioned criteria or one of the aforementioned algorithms are also, for example, useful in the simultaneous screening and functional analysis of multiple genes and gene families using high throughput strategies, as well as in direct gene suppression or silencing.

Development of the Algorithms

To identify siRNA sequence features that promote functionality and to quantify the importance of certain currently accepted conventional factors—such as G/C content and target site accessibility—the inventors synthesized an siRNA panel consisting of 270 siRNAs targeting three genes, Human Cyclophilin, Firefly Luciferase, and Human DBI. In all three cases, siRNAs were directed against specific regions of each gene. For Human Cyclophilin and Firefly Luciferase, ninety siRNAs were directed against a 199 bp segment of each respective mRNA. For DBI, 90 siRNAs were directed against a smaller, 109 base pair region of the mRNA. The sequences to which the siRNAs were directed are provided below.

It should be noted that in certain sequences, “t” is present. This is because many databases contain information in this manner. However, the t denotes a uracil residue in mRNA and siRNA. Any algorithm will, unless otherwise specified, process a t in a sequence as a u.

Human cyclophilin: 193-390 M60857 gttccaaaaacagtggataattttgtggccttagct SEQ. ID NO. 29 acaggagagaaaggatttggctacaaaaacagcaaa ttccatcgtgtaatcaaggacttcatgatccagggc ggagacttcaccaggggagatggcacaggaggaaag agcatctacggtgagcgcttccccgatgagaacttc aaactgaagcactacgggcctggctggg:

Firefly luciferase: 1434-1631, U47298 (pGL3, Promega) tgaacttcccgccgccgttgttgttttggagcacgg SEQ. ID NO. 30 aaagacgatgacggaaaaagagatcgtggattacgt cgccagtcaagtaacaaccgcgaaaaagttgcgcgg aggagttgtgtttgtggacgaagtaccgaaaggtct taccggaaaactcgacgcaagaaaaatcagagagat cctcataaaggccaagaagg:

DBI, NM_(—)020548 (202-310) (Every Position) acgggcaaggccaagtgggatgcctggaatgagc SEQ. ID NO. 0031 tgaaagggacttccaaggaagatgccatgaaagc ttacatcaacaaagtagaagagctaaagaaaaaa tacggg: A list of the siRNAs appears in Table III (see Examples Section, Example II)

The set of duplexes was analyzed to identify correlations between siRNA functionality and other biophysical or thermodynamic properties. When the siRNA panel was analyzed in functional and non-functional subgroups, certain nucleotides were much more abundant at certain positions in functional or non-functional groups. More specifically, the frequency of each nucleotide at each position in highly functional siRNA duplexes was compared with that of nonfunctional duplexes in order to assess the preference for or against any given nucleotide at every position. These analyses were used to determine important criteria to be included in the siRNA algorithms (Formulas VIII, IX, and X).

The data set was also analyzed for distinguishing biophysical properties of siRNAs in the functional group, such as optimal percent of GC content, propensity for internal structures and regional thermodynamic stability. Of the presented criteria, several are involved in duplex recognition, RISC activation/duplex unwinding, and target cleavage catalysis.

The original data set that was the source of the statistically derived criteria is shown in FIG. 2. Additionally, this figure shows that random selection yields siRNA duplexes with unpredictable and widely varying silencing potencies as measured in tissue culture using HEK293 cells. In the figure, duplexes are plotted such that each x-axis tick-mark represents an individual siRNA, with each subsequent siRNA differing in target position by two nucleotides for Human Cyclophilin B and Firefly Luciferase, and by one nucleotide for Human DBI. Furthermore, the y-axis denotes the level of target expression remaining after transfection of the duplex into cells and subsequent silencing of the target.

siRNA identified and optimized in this document work equally well in a wide range of cell types. FIG. 3 a shows the evaluation of thirty siRNAs targeting the DBI gene in three cell lines derived from different tissues. Each DBI siRNA displays very similar functionality in HEK293 (ATCC, CRL-1573, human embryonic kidney), HeLa (ATCC, CCL-2, cervical epithelial adenocarcinoma) and DU145 (HTB-81, prostate) cells as deterimined by the B-DNA assay. Thus, siRNA functionality is determined by the primary sequence of the siRNA and not by the intracellular environment. Additionally, it should be noted that although the present invention provides for a determination of the functionality of siRNA for a given target, the same siRNA may silence more than one gene. For example, the complementary sequence of the silencing siRNA may be present in more than one gene. Accordingly, in these circumstances, it may be desirable not to use the siRNA with highest SMARTscore™. In such circumstances, it may be desirable to use the siRNA with the next highest SMARTscore™.

To determine the relevance of G/C content in siRNA function, the G/C content of each duplex in the panel was calculated and the functional classes of siRNAs (<F50,≧F50, ≧F80,≧F95 where F refers to the percent gene silencing) were sorted accordingly. The majority of the highly-functional siRNAs (≧F95) fell within the G/C content range of 36-52% (FIG. 3B). Twice as many non-functional (<F50) duplexes fell within the high G/C content groups (>57% GC content) compared to the 36%-52% group. The group with extremely low GC content (26% or less) contained a higher proportion of non-functional siRNAs and no highly-functional siRNAs. The G/C content range of 30%-52% was therefore selected as Criterion I for siRNA functionality, consistent with the observation that a G/C range 30%-70% promotes efficient RNAi targeting. Application of this criterion alone provided only a marginal increase in the probability of selecting functional siRNAs from the panel: selection of F50 and F95 siRNAs was improved by 3.6% and 2.2%, respectively. The siRNA panel presented here permitted a more systematic analysis and quantification of the importance of this criterion than that used previously.

A relative measure of local internal stability is the A/U base pair (bp) content; therefore, the frequency of A/U bp was determined for each of the five terminal positions of the duplex (5′ sense (S)/5′ antisense (AS)) of all siRNAs in the panel. Duplexes were then categorized by the number of A/U bp in positions 1-5 and 15-19 of the sense strand. The thermodynamic flexibility of the duplex 5′-end (positions 1-5; S) did not appear to correlate appreciably with silencing potency, while that of the 3′-end (positions 15-19; S) correlated with efficient silencing. No duplexes lacking A/U bp in positions 15-19 were functional. The presence of one A/U bp in this region conferred some degree of functionality, but the presence of three or more A/Us was preferable and therefore defined as Criterion II. When applied to the test panel, only a marginal increase in the probability of functional siRNA selection was achieved: a 1.8% and 2.3% increase for F50 and F95 duplexes, respectively (Table IV).

The complementary strands of siRNAs that contain internal repeats or palindromes may form internal fold-back structures. These hairpin-like structures exist in equilibrium with the duplexed form effectively reducing the concentration of functional duplexes. The propensity to form internal hairpins and their relative stability can be estimated by predicted melting temperatures. High Tm reflects a tendency to form hairpin structures. Lower Tm values indicate a lesser tendency to form hairpins. When the functional classes of siRNAs were sorted by T_(m) (FIG. 3 c), the following trends were identified: duplexes lacking stable internal repeats were the most potent silencers (no F95 duplex with predicted hairpin structure T_(m)>60° C.). In contrast, about 60% of the duplexes in the groups having internal hairpins with calculated T_(m) values less than 20° C. were F80. Thus, the stability of internal repeats is inversely proportional to the silencing effect and defines Criterion III (predicted hairpin structure T_(m)≦20° C.).

Sequence-Based Determinants of siRNA Functionality

When the siRNA panel was sorted into functional and non-functional groups, the frequency of a specific nucleotide at each position in a functional siRNA duplex was compared with that of a nonfunctional duplex in order to assess the preference for or against a certain nucleotide. FIG. 4 shows the results of these queries and the subsequent resorting of the data set (from FIG. 2). The data is separated into two sets: those duplexes that meet the criteria, a specific nucleotide in a certain position—grouped on the left (Selected) and those that do not—grouped on the right (Eliminated). The duplexes are further sorted from most functional to least functional with the y-axis of FIG. 4 a-e representing the % expression i.e., the amount of silencing that is elicited by the duplex (Note: each position on the X-axis represents a different duplex). Statistical analysis revealed correlations between silencing and several sequence-related properties of siRNAs. FIG. 4 and Table IV show quantitative analysis for the following five sequence-related properties of siRNA: (A) an A at position 19 of the sense strand; (B) an A at position 3 of the sense strand; (C) a U at position 10 of the sense strand; (D) a base other than G at position 13 of the sense strand; and (E) a base other than C at position 19 of the sense strand.

When the siRNAs in the panel were evaluated for the presence of an A at position 19 of the sense strand, the percentage of non-functional duplexes decreased from 20% to 11.8%, and the percentage of F95 duplexes increased from 21.7% to 29.4% (Table IV). Thus, the presence of an A in this position defined Criterion IV.

Another sequence-related property correlated with silencing was the presence of an A in position 3 of the sense strand (FIG. 4 b). Of the siRNAs with A3, 34.4% were F95, compared with 21.7% randomly selected siRNAs. The presence of a U base in position 10 of the sense strand exhibited an even greater impact (FIG. 4 c). Of the duplexes in this group, 41.7% were F95. These properties became criteria V and VI, respectively.

Two negative sequence-related criteria that were identified also appear on FIG. 4. The absence of a G at position 13 of the sense strand, conferred a marginal increase in selecting functional duplexes (FIG. 4 d). Similarly, lack of a C at position 19 of the sense strand also correlated with functionality (FIG. 4 e). Thus, among functional duplexes, position 19 was most likely occupied by A, and rarely occupied by C. These rules were defined as criteria VII and VIII, respectively.

Application of each criterion individually provided marginal but statistically significant increases in the probability of selecting a potent siRNA. Although the results were informative, the inventors sought to maximize potency and therefore consider multiple criteria or parameters. Optimization is particularly important when developing therapeutics. Interestingly, the probability of selecting a functional siRNA based on each thermodynamic criteria was 2%-4% higher than random, but 4%-8% higher for the sequence-related determinates. Presumably, these sequence-related increases reflect the complexity of the RNAi mechanism and the multitude of protein-RNA interactions that are involved in RNAi-mediated silencing. TABLE IV Improvement Criterion % Functional over Random I. 30%-52% G/C content <F50 16.4% −3.6%   ≧F50 83.6% 3.6% ≧F80 60.4% 4.3% ≧F95 23.9% 2.2% II. At least 3 A/U bases at positions <F50 18.2% −1.8%   15-19 of the sense strand ≧F50 81.8% 1.8% ≧F80 59.7% 3.6% ≧F95 24.0% 2.3% III. Absence of internal repeats, <F50 16.7% −3.3%   as measured by T_(m) of ≧F50 83.3% 3.3% secondary structure ≦20° C. ≧F80 61.1% 5.0% ≧F95 24.6% 2.9% IV. An A base at position 19 <F50 11.8% −8.2%   of the sense strand ≧F50 88.2% 8.2% ≧F80 75.0% 18.9%  ≧F95 29.4% 7.7% V. An A base at position 3 <F50 17.2% −2.8%   of the sense strand ≧F50 82.8% 2.8% ≧F80 62.5% 6.4% ≧F95 34.4% 12.7%  VI. A U base at position 10 <F50 13.9% −6.1%   of the sense strand ≧F50 86.1% 6.1% ≧F80 69.4% 13.3%  ≧F95 41.7%  20% VII. A base other than C at <F50 18.8% −1.2%   position 19 of the sense strand ≧F50 81.2% 1.2% ≧F80 59.7% 3.6% ≧F95 24.2% 2.5% VIII. A base other than G at <F50 15.2% −4.8%   position 13 of the sense strand ≧F50 84.8% 4.8% ≧F80 61.4% 5.3% ≧F95 26.5% 4.8% The siRNA Selection Algorithm

In an effort to improve selection further, all identified criteria, including but not limited to those listed in Table IV were combined into the algorithms embodied in Formula VIII, Formula IX, and Formula X. Each siRNA was then assigned a score (referred to as a SMARTscore™) according to the values derived from the formulas. Duplexes that scored higher than 0 or −20 (unadjusted), for Formulas VIII and IX, respectively, effectively selected a set of functional siRNAs and excluded all non-functional siRNAs. Conversely, all duplexes scoring lower than 0 and −20 (minus 20) according to formulas VIII and IX, respectively, contained some functional siRNAs but included all non-functional siRNAs. A graphical representation of this selection is shown in FIG. 5. It should be noted that the scores derived from the algorithm can also be provided as “adjusted” scores. To convert Formula VIII unadjusted scores into adjusted scores it is necessary to use the following equation: (160+unadjusted score)/2.25 When this takes place, an unadjusted score of “0” (zero) is converted to 75. Similarly, unadjusted scores for Formula X can be converted to adjusted scores. In this instance, the following equation is applied: (228+unadjusted score)/3.56 When these manipulations take place, an unadjusted score of 38 is converted to an adjusted score of 75.

The methods for obtaining the seven criteria embodied in Table IV are illustrative of the results of the process used to develop the information for Formulas VIII, IX, and X. Thus similar techniques were used to establish the other variables and their multipliers. As described above, basic statistical methods were use to determine the relative values for these multipliers.

To determine the value for “Improvement over Random” the difference in the frequency of a given attribute (e.g., GC content, base preference) at a particular position is determined between individual functional groups (e.g., <F50) and the total siRNA population studied (e.g., 270 siRNA molecules selected randomly). Thus, for instance, in Criterion I (30%-52% GC content) members of the <F50 group were observed to have GC contents between 30-52% in 16.4% of the cases. In contrast, the total group of 270 siRNAs had GC contents in this range, 20% of the time. Thus for this particular attribute, there is a small negative correlation between 30%-52% GC content and this functional group (i.e., 16.4%-20%=−3.6%). Similarly, for Criterion VI, (a “U” at position 10 of the sense strand), the >F95 group contained a “U” at this position 41.7% of the time. In contrast, the total group of 270 siRNAs had a “U” at this position 21.7% of the time, thus the improvement over random is calculated to be 20% (or 41.7%-21.7%).

Identifying the Average Internal Stability Profile of Strong siRNA

In order to identify an internal stability profile that is characteristic of strong siRNA, 270 different siRNAs derived from the cyclophilin B, the diazepam binding inhibitor (DBI), and the luciferase gene were individually transfected into HEK293 cells and tested for their ability to induce RNAi of the respective gene. Based on their performance in the in vivo assay, the sequences were then subdivided into three groups, (i) >95% silencing; (ii) 80-95% silencing; and (iii) less than 50% silencing. Sequences exhibiting 51-84% silencing were eliminated from further consideration to reduce the difficulties in identifying relevant thermodynamic patterns.

Following the division of siRNA into three groups, a statistical analysis was performed on each member of each group to determine the average internal stability profile (AISP) of the siRNA. To accomplish this the Oligo 5.0 Primer Analysis Software and other related statistical packages (e.g., Excel) were exploited to determine the internal stability of pentamers using the nearest neighbor method described by Freier et al., (1986) Improved free-energy parameters for predictions of RNA duplex stability, Proc Natl. Acad. Sci. U.S.A. 83(24): 9373-7. Values for each group at each position were then averaged, and the resulting data were graphed on a linear coordinate system with the Y-axis expressing the ΔG (free energy) values in kcal/mole and the X-axis identifying the position of the base relative to the 5′ end.

The results of the analysis identified multiple key regions in siRNA molecules that were critical for successful gene silencing. At the 3′-most end of the sense strand (5′antisense), highly functional siRNA (>95% gene silencing, see FIG. 6 a, >F95) have a low internal stability (AISP of position 19=˜7.6 kcal/mol). In contrast low-efficiency siRNA (i.e., those exhibiting less than 50% silencing, <F50) display a distinctly different profile, having high ΔG values (˜−8.4 kcal/mol) for the same position. Moving in a 5′ (sense strand) direction, the internal stability of highly efficient siRNA rises (position 12=˜−8.3 kcal/mole) and then drops again (position 7=˜−7.7 kcal/mol) before leveling off at a value of approximately −8.1 kcal/mol for the 5′ terminus. siRNA with poor silencing capabilities show a distinctly different profile. While the AISP value at position 12 is nearly identical with that of strong siRNAs, the values at positions 7 and 8 rise considerably, peaking at a high of ˜−9.0 kcal/mol. In addition, at the 5′ end of the molecule the AISP profile of strong and weak siRNA differ dramatically. Unlike the relatively strong values exhibited by siRNA in the >95% silencing group, siRNAs that exhibit poor silencing activity have weak AISP values (−7.6, −7.5, and −7.5 kcal/mol for positions 1, 2 and 3 respectively).

Overall the profiles of both strong and weak siRNAs form distinct sinusoidal shapes that are roughly 180° out-of-phase with each other. While these thermodynamic descriptions define the archetypal profile of a strong siRNA, it will likely be the case that neither the ΔG values given for key positions in the profile or the absolute position of the profile along the Y-axis (i.e., the ΔG-axis) are absolutes. Profiles that are shifted upward or downward (i.e., having on an average, higher or lower values at every position) but retain the relative shape and position of the profile along the X-axis can be foreseen as being equally effective as the model profile described here. Moreover, it is likely that siRNA that have strong or even stronger gene-specific silencing effects might have exaggerated ΔG values (either higher or lower) at key positions. Thus, for instance, it is possible that the 5′-most position of the sense strand (position 19) could have ΔG values of 7.4 kcal/mol or lower and still be a strong siRNA if, for instance, a G-C→G-T/U mismatch were substituted at position 19 and altered duplex stability. Similarly, position 12 and position 7 could have values above 8.3 kcal/mol and below 7.7 kcal/mole, respectively, without abating the silencing effectiveness of the molecule. Thus, for instance, at position 12, a stabilizing chemical modification (e.g., a chemical modification of the 2′ position of the sugar backbone) could be added that increases the average internal stability at that position. Similarly, at position 7, mismatches similar to those described previously could be introduced that would lower the ΔG values at that position.

Lastly, it is important to note that while functional and non-functional siRNA were originally defined as those molecules having specific silencing properties, both broader or more limiting parameters can be used to define these molecules. As used herein, unless otherwise specified, “non-functional siRNA” are defined as those siRNA that induce less than 50% (<50%) target silencing, “semi-functional siRNA” induce 50-79% target silencing, “functional siRNA” are molecules that induce 80-95% gene silencing, and “highly-functional siRNA” are molecules that induce great than 95% gene silencing. These definitions are not intended to be rigid and can vary depending upon the design and needs of the application. For instance, it is possible that a researcher attempting to map a gene to a chromosome using a functional assay, may identify an siRNA that reduces gene activity by only 30%. While this level of gene silencing may be “non-functional” for, e.g., therapeutic needs, it is sufficient for gene mapping purposes and is, under these uses and conditions, “functional.” For these reasons, functional siRNA can be defined as those molecules having greater than 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, or 90% silencing capabilities at 100 nM transfection conditions. Similarly, depending upon the needs of the study and/or application, non-functional and semi-functional siRNA can be defined as having different parameters. For instance, semi-functional siRNA can be defined as being those molecules that induce 20%, 30%, 40%, 50%, 60%, or 70% silencing at 100 nM transfection conditions. Similarly, non-functional siRNA can be defined as being those molecules that silence gene expression by less than 70%, 60%, 50%, 40%, 30%, or less. Nonetheless, unless otherwise stated, the descriptions stated in the “Definitions” section of this text should be applied.

Functional attributes can be assigned to each of the key positions in the AISP of strong siRNA. The low 5′ (sense strand) AISP values of strong siRNAs may be necessary for determining which end of the molecule enters the RISC complex. In contrast, the high and low AISP values observed in the central regions of the molecule may be critical for siRNA-target mRNA interactions and product release, respectively.

If the AISP values described above accurately define the thermodynamic parameters of strong siRNA, it would be expected that similar patterns would be observed in strong siRNA isolated from nature. Natural siRNAs exist in a harsh, RNase-rich environment and it can be hypothesized that only those siRNA that exhibit heightened affinity for RISC (i.e., siRNA that exhibit an average internal stability profile similar to those observed in strong siRNA) would survive in an intracellular environment. This hypothesis was tested using GFP-specific siRNA isolated from N. benthamiana. Llave et al. (2002) Endogenous and Silencing-Associated Small RNAs in Plants, The Plant Cell 14, 1605-1619, introduced long double-stranded GFP-encoding RNA into plants and subsequently re-isolated GFP-specific siRNA from the tissues. The AISP of fifty-nine of these GFP-siRNA were determined, averaged, and subsequently plotted alongside the AISP profile obtained from the cyclophilin B/DBI/luciferase siRNA having >90% silencing properties (FIG. 6 b). Comparison of the two groups show that profiles are nearly identical. This finding validates the information provided by the internal stability profiles and demonstrates that: (1) the profile identified by analysis of the cyclophilin B/DBI/luciferase siRNAs are not gene specific; and (2) AISP values can be used to search for strong siRNAs in a variety of species.

Both chemical modifications and base-pair mismatches can be incorporated into siRNA to alter the duplex's AISP and functionality. For instance, introduction of mismatches at positions 1 or 2 of the sense strand destabilized the 5′ end of the sense strand and increases the functionality of the molecule (see Luc, FIG. 7). Similarly, addition of 2′-O-methyl groups to positions 1 and 2 of the sense strand can also alter the AISP and (as a result) increase both the functionality of the molecule and eliminate off-target effects that results from sense strand homology with the unrelated targets (FIGS. 8 a, 8 b).

Rationale for Criteria in a Biological Context

The fate of siRNA in the RNAi pathway may be described in 5 major steps: (1) duplex recognition and pre-RISC complex formation; (2) ATP-dependent duplex unwinding/strand selection and RISC activation; (3) mRNA target identification; (4) mRNA cleavage, and (5) product release (FIG. 1). Given the level of nucleic acid-protein interactions at each step, siRNA functionality is likely influenced by specific biophysical and molecular properties that promote efficient interactions within the context of the multi-component complexes. Indeed, the systematic analysis of the siRNA test set identified multiple factors that correlate well with functionality. When combined into a single algorithm, they proved to be very effective in selecting active siRNAs.

The factors described here may also be predictive of key functional associations important for each step in RNAi. For example, the potential formation of internal hairpin structures correlated negatively with siRNA functionality. Complementary strands with stable internal repeats are more likely to exist as stable hairpins thus decreasing the effective concentration of the functional duplex form. This suggests that the duplex is the preferred conformation for initial pre-RISC association. Indeed, although single complementary strands can induce gene silencing, the effective concentration required is at least two orders of magnitude higher than that of the duplex form.

siRNA-pre-RISC complex formation is followed by an ATP-dependent duplex unwinding step and “activation” of the RISC. The siRNA functionality was shown to correlate with overall low internal stability of the duplex and low internal stability of the 3′ sense end (or differential internal stability of the 3′ sense compare to the 5′ sense strand), which may reflect strand selection and entry into the RISC. Overall duplex stability and low internal stability at the 3′ end of the sense strand were also correlated with siRNA functionality. Interestingly, siRNAs with very high and very low overall stability profiles correlate strongly with non-functional duplexes. One interpretation is that high internal stability prevents efficient unwinding while very low stability reduces siRNA target affinity and subsequent mRNA cleavage by the RISC.

Several criteria describe base preferences at specific positions of the sense strand and are even more intriguing when considering their potential mechanistic roles in target recognition and mRNA cleavage. Base preferences for A at position 19 of the sense strand but not C, are particularly interesting because they reflect the same base preferences observed for naturally occurring miRNA precursors. That is, among the reported miRNA precursor sequences 75% contain a U at position 1 which corresponds to an A in position 19 of the sense strand of siRNAs, while G was under-represented in this same position for miRNA precursors. These observations support the hypothesis that both miRNA precursors and siRNA duplexes are processed by very similar if not identical protein machinery. The functional interpretation of the predominance of a U/A base pair is that it promotes flexibility at the 5′antisense ends of both siRNA duplexes and miRNA precursors and facilitates efficient unwinding and selective strand entrance into an activated RISC.

Among the criteria associated with base preferences that are likely to influence mRNA cleavage or possibly product release, the preference for U at position 10 of the sense strand exhibited the greatest impact, enhancing the probability of selecting an F80 sequence by 13.3%. Activated RISC preferentially cleaves target mRNA between nucleotides 10 and 11 relative to the 5′ end of the complementary targeting strand. Therefore, it may be that U, the preferred base for most endoribonucleases, at this position supports more efficient cleavage. Alternatively, a U/A bp between the targeting siRNA strand and its cognate target mRNA may create an optimal conformation for the RISC-associated “slicing” activity.

Post Algorithm Filters

According to another embodiment, the output of any one of the formulas previously listed can be filtered to remove or select for siRNAs containing undesirable or desirable motifs or properties, respectively. In one example, sequences identified by any of the formulas can be filtered to remove any and all sequences that induce toxicity or cellular stress. Introduction of an siRNA containing a toxic motif into a cell can induce cellular stress and/or cell death (apoptosis) which in turn can mislead researchers into associating a particular (e.g., nonessential) gene with, e.g., an essential function. Alternatively, sequences generated by any of the before mentioned formulas can be filtered to identify and retain duplexes that contain toxic motifs. Such duplexes may be valuable from a variety of perspectives including, for instance, uses as therapeutic molecules. A variety of toxic motifs exist and can exert their influence on the cell through RNAi and non-RNAi pathways. Examples of toxic motifs are explained more fully in commonly assigned U.S. Provisional Patent Application Ser. No. 60/538,874, entitled “Identification of Toxic Sequences,” filed Jan. 23, 2004. Briefly, toxic motifs include A/G UUU A/G/U, G/C AAA G/C, and GCCA, or a complement of any of the foregoing.

In another instance, sequences identified by any of the before mentioned formulas can be filtered to identify duplexes that contain motifs (or general properties) that provide serum stability or induce serum instability. In one envisioned application of siRNA as therapeutic molecules, duplexes targeting disease-associated genes will be introduced into patients intravenously. As the half-life of single and double stranded RNA in serum is short, post-algorithm filters designed to select molecules that contain motifs that enhance duplex stability in the presence of serum and/or (conversely) eliminate duplexes that contain motifs that destabilize siRNA in the presence of serum, would be beneficial.

In another instance, sequences identified by any of the before mentioned formulas can be filtered to identify duplexes that are hyperfunctional. Hyperfunctional sequences are defined as those sequences that (1) induce greater than 95% silencing of a specific target when they are transfected at subnanomolar concentrations (i.e., less than one nanomolar); and/or (2) induce functional (or better) levels of silencing for greater than 96 hours. Filters that identify hyperfunctional molecules can vary widely. In one example, the top ten, twenty, thirty, or forty siRNA can be assessed for the ability to silence a given target at, e.g., concentrations of 1 nM and 0.5 nM to identify hyperfunctional molecules.

Pooling

According to another embodiment, the present invention provides a pool of at least two siRNAs, preferably in the form of a kit or therapeutic reagent, wherein one strand of each of the siRNAs, the sense strand comprises a sequence that is substantially similar to a sequence within a target mRNA. The opposite strand, the antisense strand, will preferably comprise a sequence that is substantially complementary to that of the target mRNA. More preferably, one strand of each siRNA will comprise a sequence that is identical to a sequence that is contained in the target mRNA. Most preferably, each siRNA will be 19 base pairs in length, and one strand of each of the siRNAs will be 100% complementary to a portion of the target mRNA.

By increasing the number of siRNAs directed to a particular target using a pool or kit, one is able both to increase the likelihood that at least one siRNA with satisfactory functionality will be included, as well as to benefit from additive or synergistic effects. Further, when two or more siRNAs directed against a single gene do not have satisfactory levels of functionality alone, if combined, they may satisfactorily promote degradation of the target messenger RNA and successfully inhibit translation. By including multiple siRNAs in the system, not only is the probability of silencing increased, but the economics of operation are also improved when compared to adding different siRNAs sequentially. This effect is contrary to the conventional wisdom that the concurrent use of multiple siRNA will negatively impact gene silencing (e.g., Holen, T. et al. (2003) “Similar behavior of single strand and double strand siRNAs suggests they act through a common RNAi pathway.” NAR 31: 2401-21407).

In fact, when two siRNAs were pooled together, 54% of the pools of two siRNAs induced more than 95% gene silencing. Thus, a 2.5-fold increase in the percentage of functionality was achieved by randomly combining two siRNAs. Further, over 84% of pools containing two siRNAs induced more than 80% gene silencing.

More preferably, the kit is comprised of at least three siRNAs, wherein one strand of each siRNA comprises a sequence that is substantially similar to a sequence of the target mRNA and the other strand comprises a sequence that is substantially complementary to the region of the target mRNA. As with the kit that comprises at least two siRNAs, more preferably one strand will comprise a sequence that is identical to a sequence that is contained in the mRNA and another strand that is 100% complementary to a sequence that is contained in the mRNA. During experiments, when three siRNAs were combined together, 60% of the pools induced more than 95% gene silencing and 92% of the pools induced more than 80% gene silencing.

Further, even more preferably, the kit is comprised of at least four siRNAs, wherein one strand of each siRNA comprises a sequence that is substantially similar to a region of the sequence of the target mRNA, and the other strand comprises a sequence that is substantially complementary to the region of the target mRNA. As with the kit or pool that comprises at least two siRNAs, more preferably one strand of each of the siRNA duplexes will comprise a sequence that is identical to a sequence that is contained in the mRNA, and another strand that is 100% complementary to a sequence that is contained in the mRNA.

Additionally, kits and pools with at least five, at least six, and at least seven siRNAs may also be useful with the present invention. For example, pools of five siRNA induced 95% gene silencing with 77% probability and 80% silencing with 98.8% probability. Thus, pooling of siRNAs together can result in the creation of a target-specific silencing reagent with almost a 99% probability of being functional. The fact that such high levels of success are achievable using such pools of siRNA, enables one to dispense with costly and time-consuming target-specific validation procedures.

For this embodiment, as well as the other aforementioned embodiments, each of the siRNAs within a pool will preferably comprise 18-30 base pairs, more preferably 18-25 base pairs, and most preferably 19 base pairs. Within each siRNA, preferably at least 18 contiguous bases of the antisense strand will be 100% complementary to the target mRNA. More preferably, at least 19 contiguous bases of the antisense strand will be 100% complementary to the target mRNA. Additionally, there may be overhangs on either the sense strand or the antisense strand, and these overhangs may be at either the 5′ end or the 3′ end of either of the strands, for example there may be one or more overhangs of 1-6 bases. When overhangs are present, they are not included in the calculation of the number of base pairs. The two nucleotide 3′ overhangs mimic natural siRNAs and are commonly used but are not essential. Preferably, the overhangs should consist of two nucleotides, most often dTdT or UU at the 3′ end of the sense and antisense strand that are not complementary to the target sequence. The siRNAs may be produced by any method that is now known or that comes to be known for synthesizing double stranded RNA that one skilled in the art would appreciate would be useful in the present invention. Preferably, the siRNAs will be produced by Dharmacon's proprietary ACE® technology. However, other methods for synthesizing siRNAs are well known to persons skilled in the art and include, but are not limited to, any chemical synthesis of RNA oligonucleotides, ligation of shorter oligonucleotides, in vitro transcription of RNA oligonucleotides, the use of vectors for expression within cells, recombinant Dicer products and PCR products.

The siRNA duplexes within the aforementioned pools of siRNAs may correspond to overlapping sequences within a particular mRNA, or non-overlapping sequences of the mRNA. However, preferably they correspond to non-overlapping sequences. Further, each siRNA may be selected randomly, or one or more of the siRNA may be selected according to the criteria discussed above for maximizing the effectiveness of siRNA.

Included in the definition of siRNAs are siRNAs that contain substituted and/or labeled nucleotides that may, for example, be labeled by radioactivity, fluorescence or mass. The most common substitutions are at the 2′ position of the ribose sugar, where moieties such as H (hydrogen) F, NH₃, OCH₃ and other O- alkyl, alkenyl, alkynyl, and orthoesters, may be substituted, or in the phosphorous backbone, where sulfur, amines or hydrocarbons may be substituted for the bridging of non-bridging atoms in the phosphodiester bond. Examples of modified siRNAs are explained more fully in commonly assigned U.S. patent application Ser. No. 10/613,077, filed Jul. 1, 2003.

Additionally, as noted above, the cell type into which the siRNA is introduced may affect the ability of the siRNA to enter the cell; however, it does not appear to affect the ability of the siRNA to function once it enters the cell. Methods for introducing double-stranded RNA into various cell types are well known to persons skilled in the art.

As persons skilled in the art are aware, in certain species, the presence of proteins such as RdRP, the RNA-dependent RNA polymerase, may catalytically enhance the activity of the siRNA. For example, RdRP propagates the RNAi effect in C. elegans and other non-mammalian organisms. In fact, in organisms that contain these proteins, the siRNA may be inherited. Two other proteins that are well studied and known to be a part of the machinery are members of the Argonaute family and Dicer, as well as their homologues. There is also initial evidence that the RISC complex might be associated with the ribosome so the more efficiently translated mRNAs will be more susceptible to silencing than others.

Another very important factor in the efficacy of siRNA is mRNA localization. In general, only cytoplasmic mRNAs are considered to be accessible to RNAi to any appreciable degree. However, appropriately designed siRNAs, for example, siRNAs modified with internucleotide linkages or 2′-O-methyl groups, may be able to cause silencing by acting in the nucleus. Examples of these types of modifications are described in commonly assigned U.S. patent application Ser. Nos. 10/431,027 and 10/613,077.

As described above, even when one selects at least two siRNAs at random, the effectiveness of the two may be greater than one would predict based on the effectiveness of two individual siRNAs. This additive or synergistic effect is particularly noticeable as one increases to at least three siRNAs, and even more noticeable as one moves to at least four siRNAs. Surprisingly, the pooling of the non-functional and semi-functional siRNAs, particularly more than five siRNAs, can lead to a silencing mixture that is as effective if not more effective than any one particular functional siRNA.

Within the kits of the present invention, preferably each siRNA will be present in a concentration of between 0.001 and 200 μM, more preferably between 0.01 and 200 nM, and most preferably between 0.1 and 10 nM.

In addition to preferably comprising at least four or five siRNAs, the kits of the present invention will also preferably comprise a buffer to keep the siRNA duplex stable. Persons skilled in the art are aware of buffers suitable for keeping siRNA stable. For example, the buffer may be comprised of 100 mM KCl, 30 mM HEPES-pH 7.5, and 1 mM MgCl₂. Alternatively, kits might contain complementary strands that contain any one of a number of chemical modifications (e.g., a 2′-O-ACE) that protect the agents from degradation by nucleases. In this instance, the user may (or may not) remove the modifying protective group (e.g., deprotect) before annealing the two complementary strands together.

By way of example, the kits may be organized such that pools of siRNA duplexes are provided on an array or microarray of wells or drops for a particular gene set or for unrelated genes. The array may, for example, be in 96 wells, 384 wells or 1284 wells arrayed in a plastic plate or on a glass slide using techniques now known or that come to be known to persons skilled in the art. Within an array, preferably there will be controls such as functional anti-lamin A/C, cyclophilin and two siRNA duplexes that are not specific to the gene of interest.

In order to ensure stability of the siRNA pools prior to usage, they may be retained in lyophilized form at minus twenty degrees (−20° C.) until they are ready for use. Prior to usage, they should be resuspended; however, even once resuspended, for example, in the aforementioned buffer, they should be kept at minus twenty degrees, (−20° C.) until used. The aforementioned buffer, prior to use, may be stored at approximately 4° C. or room temperature. Effective temperatures at which to conduct transfections are well known to persons skilled in the art and include for example, room temperature.

The kits may be applied either in vivo or in vitro. Preferably, the siRNA of the pools or kits is applied to a cell through transfection, employing standard transfection protocols. These methods are well known to persons skilled in the art and include the use of lipid-based carriers, electroporation, cationic carriers, and microinjection. Further, one could apply the present invention by synthesizing equivalent DNA sequences (either as two separate, complementary strands, or as hairpin molecules) instead of siRNA sequences and introducing them into cells through vectors. Once in the cells, the cloned DNA could be transcribed, thereby forcing the cells to generate the siRNA. Examples of vectors suitable for use with the present application include but are not limited to the standard transient expression vectors, adenoviruses, retroviruses, lentivirus-based vectors, as well as other traditional expression vectors. Any vector that has an adequate siRNA expression and procession module may be used. Furthermore, certain chemical modifications to siRNAs, including but not limited to conjugations to other molecules, may be used to facilitate delivery. For certain applications it may be preferable to deliver molecules without transfection by simply formulating in a physiological acceptable solution.

This embodiment may be used in connection with any of the aforementioned embodiments. Accordingly, the sequences within any pool may be selected by rational design.

Multigene Silencing

In addition to developing kits that contain multiple siRNA directed against a single gene, another embodiment includes the use of multiple siRNA targeting multiple genes. Multiple genes may be targeted through the use of high- or hyper-functional siRNA. High- or hyper-functional siRNA that exhibit increased potency, require lower concentrations to induce desired phenotypic (and thus therapeutic) effects. This circumvents RISC saturation. It therefore reasons that if lower concentrations of a single siRNA are needed for knockout or knockdown expression of one gene, then the remaining (uncomplexed) RISC will be free and available to interact with siRNA directed against two, three, four, or more, genes. Thus in this embodiment, the authors describe the use of highly functional or hyper-functional siRNA to knock out three separate genes. More preferably, such reagents could be combined to knockout four distinct genes. Even more preferably, highly functional or hyperfunctional siRNA could be used to knock out five distinct genes. Most preferably, siRNA of this type could be used to knockout or knockdown the expression of six or more genes.

Hyperfunctional siRNA

The term hyperfunctional siRNA (hf-siRNA) describes a subset of the siRNA population that induces RNAi in cells at low- or sub-nanomolar concentrations for extended periods of time. These traits, heightened potency and extended longevity of the RNAi phenotype, are highly attractive from a therapeutic standpoint. Agents having higher potency require lesser amounts of the molecule to achieve the desired physiological response, thus reducing the probability of side effects due to “off-target” interference. In addition to the potential therapeutic benefits associated with hyperfunctional siRNA, hf-siRNA are also desirable from an economic perspective. Hyperfunctional siRNA may cost less on a per-treatment basis, thus reducing overall expenditures to both the manufacturer and the consumer.

Identification of hyperfunctional siRNA involves multiple steps that are designed to examine an individual siRNA agent's concentration- and/or longevity-profiles. In one non-limiting example, a population of siRNA directed against a single gene are first analyzed using the previously described algorithm (Formula VIII). Individual siRNA are then introduced into a test cell line and assessed for the ability to degrade the target mRNA. It is important to note that when performing this step it is not necessary to test all of the siRNA. Instead, it is sufficient to test only those siRNA having the highest SMARTscores™ (i.e., SMARTscore™>−10). Subsequently, the gene silencing data is plotted against the SMARTscores™ (see FIG. 9). siRNA that (1) induce a high degree of gene silencing (i.e., they induce greater than 80% gene knockdown) and (2) have superior SMARTscores™ (i.e., a SMARTscore™ of >−10, suggesting a desirable average internal stability profile) are selected for further investigations designed to better understand the molecule's potency and longevity. In one, non-limiting study dedicated to understanding a molecule's potency, an siRNA is introduced into one (or more) cell types in increasingly diminishing concentrations (e.g., 3.0→0.3 nM). Subsequently, the level of gene silencing induced by each concentration is examined and siRNA that exhibit hyperfunctional potency (i.e., those that induce 80% silencing or greater at, e.g., picomolar concentrations) are identified. In a second study, the longevity profiles of siRNA having high (>−10) SMARTscores™ and greater than 80% silencing are examined. In one non-limiting example of how this is achieved, siRNA are introduced into a test cell line and the levels of RNAi are measured over an extended period of time (e.g., 24-168 hrs). siRNAs that exhibit strong RNA interference patterns (i.e., >80% interference) for periods of time greater than, e.g., 120 hours, are thus identified. Studies similar to those described above can be performed on any and all of the >10⁶ siRNA included in this document to further define the most functional molecule for any given gene. Molecules possessing one or both properties (extended longevity and heightened potency) are labeled “hyperfunctional siRNA,” and earmarked as candidates for future therapeutic studies.

While the example(s) given above describe one means by which hyperfunctional siRNA can be isolated, neither the assays themselves nor the selection parameters used are rigid and can vary with each family of siRNA. Families of siRNA include siRNAs directed against a single gene, or directed against a related family of genes.

The highest quality siRNA achievable for any given gene may vary considerably. Thus, for example, in the case of one gene (gene X), rigorous studies such as those described above may enable the identification of an siRNA that, at picomolar concentrations, induces 99⁺% silencing for a period of 10 days. Yet identical studies of a second gene (gene Y) may yield an siRNA that at high nanomolar concentrations (e.g., 100 nM) induces only 75% silencing for a period of 2 days. Both molecules represent the very optimum siRNA for their respective gene targets and therefore are designated “hyperfunctional.” Yet due to a variety of factors including but not limited to target concentration, siRNA stability, cell type, off-target interference, and others, equivalent levels of potency and longevity are not achievable. Thus, for these reasons, the parameters described in the before mentioned assays can vary. While the initial screen selected siRNA that had SMARTscore™ above −10 and a gene silencing capability of greater than 80%, selections that have stronger (or weaker) parameters can be implemented. Similarly, in the subsequent studies designed to identify molecules with high potency and longevity, the desired cutoff criteria (i.e., the lowest concentration that induces a desirable level of interference, or the longest period of time that interference can be observed) can vary. The experimentation subsequent to application of the rational criteria of this application is significantly reduced where one is trying to obtain a suitable hyperfunctional siRNA for, for example, therapeutic use. When, for example, the additional experimentation of the type described herein is applied by one skilled in the art with this disclosure in hand, a hyperfunctional siRNA is readily identified.

The siRNA may be introduced into a cell by any method that is now known or that comes to be known and that from reading this disclosure, persons skilled in the art would determine would be useful in connection with the present invention in enabling siRNA to cross the cellular membrane. These methods include, but are not limited to, any manner of transfection, such as, for example, transfection employing DEAE-Dextran, calcium phosphate, cationic lipids/liposomes, micelles, manipulation of pressure, microinjection, electroporation, immunoporation, use of vectors such as viruses, plasmids, cosmids, bacteriophages, cell fusions, and coupling of the polynucleotides to specific conjugates or ligands such as antibodies, antigens, or receptors, passive introduction, adding moieties to the siRNA that facilitate its uptake, and the like.

Having described the invention with a degree of particularity, examples will now be provided. These examples are not intended to and should not be construed to limit the scope of the claims in any way.

EXAMPLES

General Techniques and Nomenclatures

siRNA nomenclature. All siRNA duplexes are referred to by sense strand. The first nucleotide of the 5′-end of the sense strand is position 1, which corresponds to position 19 of the antisense strand for a 19-mer. In most cases, to compare results from different experiments, silencing was determined by measuring specific transcript mRNA levels or enzymatic activity associated with specific transcript levels, 24 hours post-transfection, with siRNA concentrations held constant at 100 nM. For all experiments, unless otherwise specified, transfection efficiency was ensured to be over 95%, and no detectable cellular toxicity was observed. The following system of nomenclature was used to compare and report siRNA-silencing functionality: “F” followed by the degree of minimal knockdown. For example, F50 signifies at least 50% knockdown, F80 means at least 80%, and so forth. For this study, all sub-F50 siRNAs were considered non-functional.

Cell culture and transfection. 96-well plates are coated with 50 μl of 50 mg/ml poly-L-lysine (Sigma) for 1 hr, and then washed 3× with distilled water before being dried for 20 min. HEK293 cells or HEK293Lucs or any other cell type of interest are released from their solid support by trypsinization, diluted to 3.5×10⁵ cells/ml, followed by the addition of 100 μL of cells/well. Plates are then incubated overnight at 37° C., 5% CO₂. Transfection procedures can vary widely depending on the cell type and transfection reagents. In one non-limiting example, a transfection mixture consisting of 2 mL Opti-MEM I (Gibco-BRL), 80 μl Lipofectamine 2000 (Invitrogen), 15 μL SUPERNasin at 20 U/μl (Ambion), and 1.5 μl of reporter gene plasmid at 1 μg/μl is prepared in 5-ml polystyrene round bottom tubes. One hundred μl of transfection reagent is then combined with 100 μl of siRNAs in polystyrene deep-well titer plates (Beckman) and incubated for 20 to 30 min at room temperature. Five hundred and fifty microliters of Opti-MEM is then added to each well to bring the final siRNA concentration to 100 nM. Plates are then sealed with parafilm and mixed. Media is removed from HEK293 cells and replaced with 95 μl of transfection mixture. Cells are incubated overnight at 37° C., 5% CO₂.

Quantification of gene knockdown. A variety of quantification procedures can be used to measure the level of silencing induced by siRNA or siRNA pools. In one non-limiting example: to measure mRNA levels 24 hrs post-transfection, QuantiGene branched-DNA (bDNA) kits (Bayer) (Wang, et al, Regulation of insulin preRNA splicing by glucose. Proc. Natl. Acad. Sci. USA 1997, 94:4360.) are used according to manufacturer instructions. To measure luciferase activity, media is removed from HEK293 cells 24 hrs post-transfection, and 50 μl of Steady-GLO reagent (Promega) is added. After 5 minutes, plates are analyzed on a plate reader.

Example I Sequences Used to Develop the Algorithm

Anti-Firefly and anti-Cyclophilin siRNAs panels (FIG. 5 a, b) sorted according to using Formula VIII predicted values. All siRNAs scoring more than 0 (formula VIII) and more then 20 (formula IX) are fully functional. All ninety sequences for each gene (and DBI) appear below in Table III. TABLE III Cyclo 1 SEQ. ID 0032 GUUCCAAAAACAGUGGAUA Cyclo 2 SEQ. ID 0033 UCCAAAAACAGUGGAUAAU Cyclo 3 SEQ. ID 0034 CAAAAACAGUGGAUAAUUU Cyclo 4 SEQ. ID 0035 AAAACAGUGGAUAAUUUUG Cyclo 5 SEQ. ID 0036 AACAGUGGAUAAUUUUGUG Cyclo 6 SEQ. ID 0037 CAGUGGAUAAUUUUGUGGC Cyclo 7 SEQ. ID 0038 GUGGAUAAUUUUGUGGCCU Cyclo 8 SEQ. ID 0039 GGAUAAUUUUGUGGCCUUA Cyclo 9 SEQ. ID 0040 AUAAUUUUGUGGCCUUAGC Cyclo 10 SEQ. ID 0041 AAUUUUGUGGCCUUAGCUA Cyclo 11 SEQ. ID 0042 UUUUGUGGCCUUAGCUACA Cyclo 12 SEQ. ID 0043 UUGUGGCCUUAGCUACAGG Cyclo 13 SEQ. ID 0044 GUGGCCUUAGCUACAGGAG Cyclo 14 SEQ. ID 0045 GGCCUUAGCUACAGGAGAG Cyclo 15 SEQ. ID 0046 CCUUAGCUACAGGAGAGAA Cyclo 16 SEQ. ID 0047 UUAGCUACAGGAGAGAAAG Cyclo 17 SEQ. ID 0048 AGCUACAGGAGAGAAAGGA Cyclo 18 SEQ. ID 0049 CUACAGGAGAGAAAGGAUU Cyclo 19 SEQ. ID 0050 ACAGGAGAGAAAGGAUUUG Cyclo 20 SEQ. ID 0051 AGGAGAGAAAGGAUUUGGC Cyclo 21 SEQ. ID 0052 GAGAGAAAGGAUUUGGCUA Cyclo 22 SEQ. ID 0053 GAGAAAGGAUUUGGCUACA Cyclo 23 SEQ. ID 0054 GAAAGGAUUUGGCUACAAA Cyclo 24 SEQ. ID 0055 AAGGAUUUGGCUACAAAAA Cyclo 25 SEQ. ID 0056 GGAUUUGGCUACAAAAACA Cyclo 26 SEQ. ID 0057 AUUUGGCUACAAAAACAGC Cyclo 27 SEQ. ID 0058 UUGGCUACAAAAACAGCAA Cyclo 28 SEQ. ID 0059 GGCUACAAAAACAGCAAAU Cyclo 29 SEQ. ID 0060 CUACAAAAACAGCAAAUUC Cyclo 30 SEQ. ID 0061 ACAAAAACAGCAAAUUCCA Cyclo 31 SEQ. ID 0062 AAAAACAGCAAAUUCCAUC Cyclo 32 SEQ. ID 0063 AAACAGCAAAUUCCAUCGU Cyclo 33 SEQ. ID 0064 ACAGCAAAUUCCAUCGUGU Cyclo 34 SEQ. ID 0065 AGCAAAUUCCAUCGUGUAA Cyclo 35 SEQ. ID 0066 CAAAUUCCAUCGUGUAAUC Cyclo 36 SEQ. ID 0067 AAUUCCAUCGUGUAAUCAA Cyclo 37 SEQ. ID 0068 UUCCAUCGUGUAAUCAAGG Cyclo 38 SEQ. ID 0069 CCAUCGUGUAAUCAAGGAC Cyclo 39 SEQ. ID 0070 AUCGUGUAAUCAAGGACUU Cyclo 40 SEQ. ID 0071 CGUGUAAUCAAGGACUUCA Cyclo 41 SEQ. ID 0072 UGUAAUCAAGGACUUCAUG Cyclo 42 SEQ. ID 0073 UAAUCAAGGACUUCAUGAU Cyclo 43 SEQ. ID 0074 AUCAAGGACUUCAUGAUCC Cyclo 44 SEQ. ID 0075 CAAGGACUUCAUGAUCCAG Cyclo 45 SEQ. ID 0076 AGGACUUCAUGAUCCAGGG Cyclo 46 SEQ. ID 0077 GACUUCAUGAUCCAGGGCG Cyclo 47 SEQ. ID 0078 CUUCAUGAUCCAGGGCGGA Cyclo 48 SEQ. ID 0079 UCAUGAUCCAGGGCGGAGA Cyclo 49 SEQ. ID 0080 AUGAUCCAGGGCGGAGACU Cyclo 50 SEQ. ID 0081 GAUCCAGGGCGGAGACUUC Cyclo 51 SEQ. ID 0082 UCCAGGGCGGAGACUUCAC Cyclo 52 SEQ. ID 0083 CAGGGCGGAGACUUCACCA Cyclo 53 SEQ. ID 0084 GGGCGGAGACUUCACCAGG Cyclo 54 SEQ. ID 0085 GCGGAGACUUCACCAGGGG Cyclo 55 SEQ. ID 0086 GGAGACUUCACCAGGGGAG Cyclo 56 SEQ. ID 0087 AGACUUCACCAGGGGAGAU Cyclo 57 SEQ. ID 0088 ACUUCACCAGGGGAGAUGG Cyclo 58 SEQ. ID 0089 UUCACCAGGGGAGAUGGCA Cyclo 59 SEQ. ID 0090 CACCAGGGGAGAUGGCACA Cyclo 60 SEQ. ID 0091 CCAGGGGAGAUGGCACAGG Cyclo 61 SEQ. ID 0092 AGGGGAGAUGGCACAGGAG Cyclo 62 SEQ. ID 0093 GGGAGAUGGCACAGGAGGA Cyclo 63 SEQ. ID 0094 GAGAUGGCACAGGAGGAAA Cyclo 64 SEQ. ID 0095 GAUGGCACAGGAGGAAAGA Cyclo 65 SEQ. ID 0431 UGGCACAGGAGGAAAGAGC Cyclo 66 SEQ. ID 0096 GCACAGGAGGAAAGAGCAU Cyclo 67 SEQ. ID 0097 ACAGGAGGAAAGAGCAUCU Cyclo 68 SEQ. ID 0098 AGGAGGAAAGAGCAUCUAC Cyclo 69 SEQ. ID 0099 GAGGAAAGAGCAUCUACGG Cyclo 70 SEQ. ID 0100 GGAAAGAGCAUCUACGGUG Cyclo 71 SEQ. ID 0101 AAAGAGCAUCUACGGUGAG Cyclo 72 SEQ. ID 0102 AGAGCAUCUACGGUGAGCG Cyclo 73 SEQ. ID 0103 AGCAUCUACGGUGAGCGCU Cyclo 74 SEQ. ID 0104 CAUCUACGGUGAGCGCUUC Cyclo 75 SEQ. ID 0105 UCUACGGUGAGCGCUUCCC Cyclo 76 SEQ. ID 0106 UACGGUGAGCGCUUCCCCG Cyclo 77 SEQ. ID 0107 CGGUGAGCGCUUCCCCGAU Cyclo 78 SEQ. ID 0108 GUGAGCGCUUCCCCGAUGA Cyclo 79 SEQ. ID 0109 GAGCGCUUCCCCGAUGAGA Cyclo 80 SEQ. ID 0110 GCGCUUCCCCGAUGAGAAC Cyclo 81 SEQ. ID 0111 GCUUCCCCGAUGAGAACUU Cyclo 82 SEQ. ID 0112 UUCCCCGAUGAGAACUUCA Cyclo 83 SEQ. ID 0113 CCCCGAUGAGAACUUCAAA Cyclo 84 SEQ. ID 0114 CCGAUGAGAACUUCAAACU Cyclo 85 SEQ. ID 0115 GAUGAGAACUUCAAACUGA Cyclo 86 SEQ. ID 0116 UGAGAACUUCAAACUGAAG Cyclo 87 SEQ. ID 0117 AGAACUUCAAACUGAAGCA Cyclo 88 SEQ. ID 0118 AACUUCAAACUGAAGCACU Cyclo 89 SEQ. ID 0119 CUUCAAACUGAAGCACUAC Cyclo 90 SEQ. ID 0120 UCAAACUGAAGCACUACGG DB 1 SEQ. ID 0121 ACGGGCAAGGCCAAGUGGG DB 2 SEQ. ID 0122 CGGGCAAGGCCAAGUGGGA DB 3 SEQ. ID 0123 GGGCAAGGCCAAGUGGGAU DB 4 SEQ. ID 0124 GGCAAGGCCAAGUGGGAUG DB 5 SEQ. ID 0125 GCAAGGCCAAGUGGGAUGC DB 6 SEQ. ID 0126 CAAGGCCAAGUGGGAUGCC DB 7 SEQ. ID 0127 AAGGCCAAGUGGGAUGCGU DB 8 SEQ. ID 0128 AGGCCAAGUGGGAUGCCUG DB 9 SEQ. ID 0129 GGCCAAGUGGGAUGCCUGG DB 10 SEQ. ID 0130 GCCAAGUGGGAUGCCUGGA DB 11 SEQ. ID 0131 CCAAGUGGGAUGCCUGGAA DB 12 SEQ. ID 0132 CAAGUGGGAUGCCUGGAAU DB 13 SEQ. ID 0133 AAGUGGGAUGCCUGGAAUG DB 14 SEQ. ID 0134 AGUGGGAUGCCUGGAAUGA DB 15 SEQ. ID 0135 GUGGGAUGCCUGGAAUGAG DB 16 SEQ. ID 0136 UGGGAUGCCUGGAAUGAGC DB 17 SEQ. ID 0137 GGGAUGCCUGGAAUGAGCU DB 18 SEQ. ID 0138 GGAUGCCUGGAAUGAGCUG DB 19 SEQ. ID 0139 GAUGCCUGGAAUGAGCUGA DB 20 SEQ. ID 0140 AUGCCUGGAAUGAGCUGAA DB 21 SEQ. ID 0141 UGCCUGGAAUGAGCUGAAA DB 22 SEQ. ID 0142 GCCUGGAAUGAGCUGAAAG DB 23 SEQ. ID 0143 CCUGGAAUGAGCUGAAAGG DB 24 SEQ. ID 0144 CUGGAAUGAGCUGAAAGGG DB 25 SEQ. ID 0145 UGGAAUGAGCUGAAAGGGA DB 26 SEQ. ID 0146 GGAAUGAGCUGAAAGGGAC DB 27 SEQ. ID 0147 GAAUGAGCUGAAAGGGACU DB 28 SEQ. ID 0148 AAUGAGCUGAAAGGGACUU DB 29 SEQ. ID 0149 AUGAGCUGAAAGGGACUUC DB 30 SEQ. ID 0150 UGAGCUGAAAGGGACUUCC DB 31 SEQ. ID 0151 GAGCUGAAAGGGACUUCCA DB 32 SEQ. ID 0152 AGCUGAAAGGGACUUCCAA DB 33 SEQ. ID 0153 GCUGAAAGGGACUUCCAAG DB 34 SEQ. ID 0154 CUGAAAGGGACUUCCAAGG DB 35 SEQ. ID 0155 UGAAAGGGACUUCCAAGGA DB 36 SEQ. ID 0156 GAAAGGGACUUCCAAGGAA DB 37 SEQ. ID 0157 AAAGGGACUUCCAAGGAAG DB 38 SEQ. ID 0158 AAGGGACUUCCAAGGAAGA DB 39 SEQ. ID 0159 AGGGACUUCCAAGGAAGAU DB 40 SEQ. ID 0160 GGGACUUCCAAGGAAGAUG DB 41 SEQ. ID 0161 GGACUUCCAAGGAAGAUGC DB 42 SEQ. ID 0162 GACUUCCAAGGAAGAUGCC DB 43 SEQ. ID 0163 ACUUCCAAGGAAGAUGCCA DB 44 SEQ. ID 0164 CUUCCAAGGAAGAUGCCAU DB 45 SEQ. ID 0165 UUCCAAGGAAGAUGCCAUG DB 46 SEQ. ID 0166 UCCAAGGAAGAUGCCAUGA DB 47 SEQ. ID 0167 CCAAGGAAGAUGCCAUGAA DB 48 SEQ. ID 0168 CAAGGAAGAUGCCAUGAAA DB 49 SEQ. ID 0169 AAGGAAGAUGCCAUGAAAG DB 50 SEQ. ID 0170 AGGAAGAUGCCAUGAAAGC DB 51 SEQ. ID 0171 GGAAGAUGCCAUGAAAGCU DB 52 SEQ. ID 0172 GAAGAUGCCAUGAAAGCUU DB 53 SEQ. ID 0173 AAGAUGCCAUGAAAGCUUA DB 54 SEQ. ID 0174 AGAUGCCAUGAAAGGUUAC DB 55 SEQ. ID 0175 GAUGCCAUGAAAGCUUACA DB 56 SEQ. ID 0176 AUGCCAUGAAAGCUUACAU DB 57 SEQ. ID 0177 UGCCAUGAAAGCUUACAUC DB 58 SEQ. ID 0178 GCCAUGAAAGCUUACAUCA DB 59 SEQ. ID 0179 CCAUGAAAGCUUACAUCAA DB 60 SEQ. ID 0180 CAUGAAAGCUUACAUCAAC DB 61 SEQ. ID 0181 AUGAAAGCUUACAUCAACA DB 62 SEQ. ID 0182 UGAAAGCUUACAUCAACAA DB 63 SEQ. ID 0183 GAAAGCUUACAUCAACAAA DB 64 SEQ. ID 0184 AAAGCUUACAUCAACAAAG DB 65 SEQ. ID 0185 AAGCUUACAUCAACAAAGU DB 66 SEQ. ID 0186 AGCUUACAUCAACAAAGUA DB 67 SEQ. ID 0187 GCUUACAUCAACAAAGUAG DB 68 SEQ. ID 0188 CUUACAUCAACAAAGUAGA DB 69 SEQ. ID 0189 UUACAUCAACAAAGUAGAA DB 70 SEQ. ID 0190 UACAUCAACAAAGUAGAAG DB 71 SEQ. ID 0191 ACAUCAACAAAGUAGAAGA DB 72 SEQ. ID 0192 CAUCAACAAAGUAGAAGAG DB 73 SEQ. ID 0193 AUCAACAAAGUAGAAGAGC DB 74 SEQ. ID 0194 UCAACAAAGUAGAAGAGCU DB 75 SEQ. ID 0195 CAACAAAGUAGAAGAGCUA DB 76 SEQ. ID 0196 AACAAAGUAGAAGAGCUAA DB 77 SEQ. ID 0197 ACAAAGUAGAAGAGCUAAA DB 78 SEQ. ID 0198 CAAAGUAGAAGAGCUAAAG DB 79 SEQ. ID 0199 AAAGUAGAAGAGCUAAAGA DB 80 SEQ. ID 0200 AAGUAGAAGAGCUAAAGAA DB 81 SEQ. ID 0201 AGUAGAAGAGCUAAAGAAA DB 82 SEQ. ID 0202 GUAGAAGAGCUAAAGAAAA DB 83 SEQ. ID 0203 UAGAAGAGCUAAAGAAAAA DB 84 SEQ. ID 0204 AGAAGAGCUAAAGAAAAAA DB 85 SEQ. ID 0205 GAAGAGCUAAAGAAAAAAU DB 86 SEQ. ID 0206 AAGAGCUAAAGAAAAAAUA DB 87 SEQ. ID 0207 AGAGCUAAAGAAAAAAUAC DB 88 SEQ. ID 0208 GAGCUAAAGAAAAAAUACG DB 89 SEQ. ID 0209 AGCUAAAGAAAAAAUACGG DB 90 SEQ. ID 0210 GCUAAAGAAAAAAUACGGG Luc 1 SEQ. ID 0211 AUCCUCAUAAAGGCCAAGA Luc 2 SEQ. ID 0212 AGAUCCUCAUAAAGGCCAA Luc 3 SEQ. ID 0213 AGAGAUCCUCAUAAAGGCG Luc 4 SEQ. ID 0214 AGAGAGAUCCUCAUAAAGG Luc 5 SEQ. ID 0215 UCAGAGAGAUCCUCAUAAA Luc 6 SEQ. ID 0216 AAUCAGAGAGAUCCUCAUA Luc 7 SEQ. ID 0217 AAAAUCAGAGAGAUCCUCA Luc 8 SEQ. ID 0218 GAAAAAUCAGAGAGAUCCU Luc 9 SEQ. ID 0219 AAGAAAAAUCAGAGAGAUC Luc 10 SEQ. ID 0220 GCAAGAAAAAUCAGAGAGA Luc 11 SEQ. ID 0221 ACGCAAGAAAAAUCAGAGA Luc 12 SEQ. ID 0222 CGACGCAAGAAAAAUCAGA Luc 13 SEQ. ID 0223 CUCGACGCAAGAAAAAUCA Luc 14 SEQ. ID 0224 AACUCGACGCAAGAAAAAU Luc 15 SEQ. ID 0225 AAAACUCGACGCAAGAAAA Luc 16 SEQ. ID 0226 GGAAAACUCGACGCAAGAA Luc 17 SEQ. ID 0227 CCGGAAAACUCGACGCAAG Luc 18 SEQ. ID 0228 UACCGGAAAACUCGACGCA Luc 19 SEQ. ID 0229 CUUACCGGAAAACUCGACG Luc 20 SEQ. ID 0230 GUCUUACCGGAAAACUCGA Luc 21 SEQ. ID 0231 AGGUCUUACCGGAAAACUC Luc 22 SEQ. ID 0232 AAAGGUCUUACCGGAAAAC Luc 23 SEQ. ID 0233 CGAAAGGUCUUACCGGAAA Luc 24 SEQ. ID 0234 ACCGAAAGGUCUUACCGGA Luc 25 SEQ. ID 0235 GUACCGAAAGGUCUUACCG Luc 26 SEQ. ID 0236 AAGUACCGAAAGGUCUUAC Luc 27 SEQ. ID 0237 CGAAGUACCGAAAGGUCUU Luc 28 SEQ. ID 0238 GACGAAGUACCGAAAGGUC Luc 29 SEQ. ID 0239 UGGACGAAGUACCGAAAGG Luc 30 SEQ. ID 0240 UGUGGACGAAGUACCGAAA Luc 31 SEQ. ID 0241 UUUGUGGACGAAGUACCGA Luc 32 SEQ. ID 0242 UGUUUGUGGACGAAGUACC Luc 33 SEQ. ID 0243 UGUGUUUGUGGACGAAGUA Luc 34 SEQ. ID 0244 GUUGUGUUUGUGGACGAAG Luc 35 SEQ. ID 0245 GAGUUGUGUUUGUGGACGA Luc 36 SEQ. ID 0246 AGGAGUUGUGUUUGUGGAC Luc 37 SEQ. ID 0247 GGAGGAGUUGUGUUUGUGG Luc 38 SEQ. ID 0248 GCGGAGGAGUUGUGUUUGU Luc 39 SEQ. ID 0249 GCGCGGAGGAGUUGUGUUU Luc 40 SEQ. ID 0250 UUGCGCGGAGGAGUUGUGU Luc 41 SEQ. ID 0251 AGUUGCGCGGAGGAGUUGU Luc 42 SEQ. ID 0252 AAAGUUGCGCGGAGGAGUU Luc 43 SEQ. ID 0253 AAAAAGUUGCGCGGAGGAG Luc 44 SEQ. ID 0254 CGAAAAAGUUGCGCGGAGG Luc 45 SEQ. ID 0255 GGCGAAAAAGUUGCGCGGA Luc 46 SEQ. ID 0256 ACCGCGAAAAAGUUGCGCG Luc 47 SEQ. ID 0257 CAACCGCGAAAAAGUUGCG Luc 48 SEQ. ID 0258 AACAACCGCGAAAAAGUUG Luc 49 SEQ. ID 0259 GUAACAACCGCGAAAAAGU Luc 50 SEQ. ID 0260 AAGUAACAACCGCGAAAAA Luc 51 SEQ. ID 0261 UCAAGUAACAACCGCGAAA Luc 52 SEQ. ID 0262 AGUCAAGUAACAACCGCGA Luc 53 SEQ. ID 0263 CCAGUCAAGUAACAACCGC Luc 54 SEQ. ID 0264 CGCCAGUCAAGUAACAACC Luc 55 SEQ. ID 0265 GUCGCCAGUCAAGUAACAA Luc 56 SEQ. ID 0266 ACGUCGCCAGUCAAGUAAC Luc 57 SEQ. ID 0267 UUACGUCGGCAGUCAAGUA Luc 58 SEQ. ID 0268 GAUUACGUCGCCAGUCAAG Luc 59 SEQ. ID 0269 UGGAUUACGUCGCCAGUCA Luc 60 SEQ. ID 0270 CGUGGAUUACGUCGCCAGU Luc 61 SEQ. ID 0271 AUCGUGGAUUACGUCGCCA Luc 62 SEQ. ID 0272 AGAUCGUGGAUUACGUCGC Luc 63 SEQ. ID 0273 AGAGAUCGUGGAUUACGUC Luc 64 SEQ. ID 0274 AAAGAGAUCGUGGAUUACG Luc 65 SEQ. ID 0275 AAAAAGAGAUCGUGGAUUA Luc 66 SEQ. ID 0276 GGAAAAAGAGAUCGUGGAU Luc 67 SEQ. ID 0277 ACGGAAAAAGAGAUCGUGG Luc 68 SEQ. ID 0278 UGACGGAAAAAGAGAUCGU Luc 69 SEQ. ID 0279 GAUGACGGAAAAAGAGAUC Luc 70 SEQ. ID 0280 ACGAUGACGGAAAAAGAGA Luc 71 SEQ. ID 0281 AGACGAUGACGGAAAAAGA Luc 72 SEQ. ID 0282 AAAGACGAUGACGGAAAAA Luc 73 SEQ. ID 0283 GGAAAGACGAUGACGGAAA Luc 74 SEQ. ID 0284 ACGGAAAGACGAUGACGGA Luc 75 SEQ. ID 0285 GCAGGGAAAGACGAUGACG Luc 76 SEQ. ID 0286 GAGCACGGAAAGACGAUGA Luc 77 SEQ. ID 0287 UGGAGCACGGAAAGACGAU Luc 78 SEQ. ID 0288 UUUGGAGCACGGAAAGACG Luc 79 SEQ. ID 0289 GUUUUGGAGCACGGAAAGA Luc 80 SEQ. ID 0290 UUGUUUUGGAGCACGGAAA Luc 81 SEQ. ID 0291 UGUUGUUUUGGAGCACGGA Luc 82 SEQ. ID 0292 GUUGUUGUUUUGGAGCAGG Luc 83 SEQ. ID 0293 CCGUUGUUGUUUUGGAGCA Luc 84 SEQ. ID 0294 CGCCGUUGUUGUUUUGGAG Luc 85 SEQ. ID 0295 GCCGCCGUUGUUGUUUUGG Luc 86 SEQ. ID 0296 CCGGCGCCGUUGUUGUUUU Luc 87 SEQ. ID 0297 UCCCGCCGCCGUUGUUGUU Luc 88 SEQ. ID 0298 CUUCCCGCCGCCGUUGUUG Luc 89 SEQ. ID 0299 AACUUCCCGCCGCCGUUGU Luc 90 SEQ. ID 0300 UGAACUUCCCGCCGCCGUU

Example II Validation of the Algorithm Using DBI, Luciferase, PLK, EGFR, and SEAP

The algorithm (Formula VIII) identified siRNAs for five genes, human DBI, firefly luciferase (fLuc), renilla luciferase (rLuc), human PLK, and human secreted alkaline phosphatase (SEAP). Four individual siRNAs were selected on the basis of their SMARTscores™ derived by analysis of their sequence using Formula VIII (all of the siRNAs would be selected with Formula IX as well) and analyzed for their ability to silence their targets' expression. In addition to the scoring, a BLAST search was conducted for each siRNA. To minimize the potential for off-target silencing effects, only those target sequences with more than three mismatches against un-related sequences were selected. Semizarov, et al, Specificity of short interfering RNA determined through gene expression signatures. Proc. Natl. Acad. Sci. U.S.A. 2003, 100:6347. These duplexes were analyzed individually and in pools of 4 and compared with several siRNAs that were randomly selected. The functionality was measured as a percentage of targeted gene knockdown as compared to controls. All siRNAs were transfected as described by the methods above at 100 nM concentration into HEK293 using Lipofectamine 2000. The level of the targeted gene expression was evaluated by B-DNA as described above and normalized to the non-specific control. FIG. 10 shows that the siRNAs selected by the algorithm disclosed herein were significantly more potent than randomly selected siRNAs. The algorithm increased the chances of identifying an F50 siRNA from 48% to 91%, and an F80 siRNA from 13% to 57%. In addition, pools of SMART siRNA silence the selected target better than randomly selected pools (see FIG. 10F).

Example III Validation of the Algorithm Using Genes Involved in Clathrin-Dependent Endocytosis

Components of clathrin-mediated endocytosis pathway are key to modulating intracellular signaling and play important roles in disease. Chromosomal rearrangements that result in fusion transcripts between the Mixed-Lineage Leukemia gene (MLL) and CALM (clathrin assembly lymphoid myeloid leukemia gene) are believed to play a role in leukemogenesis. Similarly, disruptions in Rab7 and Rab9, as well as HIP1 (Huntingtin-interacting protein), genes that are believed to be involved in endocytosis, are potentially responsible for ailments resulting in lipid storage, and neuronal diseases, respectively. For these reasons, siRNA directed against clathrin and other genes involved in the clathrin-mediated endocytotic pathway are potentially important research and therapeutic tools.

siRNAs directed against genes involved in the clathrin-mediated endocytosis pathways were selected using Formula VIII. The targeted genes were clathrin heavy chain (CHC, accession # NM_(—)004859), clathrin light chain A (CLCa, NM_(—)001833), clathrin light chain B (CLCb, NM_(—)001834), CALM (U45976), β2 subunit of AP-2 (β2, NM_(—)001282), Eps15 (NM_(—)001981), Eps15R (NM_(—)021235), dynamin II (DYNII, NM_(—)004945), Rab5a (BC001267), Rab5b (NM_(—)002868), Rab5c (AF141304), and EEA.1 (XM_(—)018197).

For each gene, four siRNAs duplexes with the highest scores were selected and a BLAST search was conducted for each of them using the Human EST database. In order to minimize the potential for off-target silencing effects, only those sequences with more than three mismatches against un-related sequences were used. All duplexes were synthesized at Dharmacon, Inc. as 21-mers with 3′-UU overhangs using a modified method of 2′-ACE chemistry, Scaringe, Advanced 5′-silyl-2′-orthoester approach to RNA oligonucleotide synthesis, Methods Enzymol 2000, 317:3, and the antisense strand was chemically phosphorylated to insure maximized activity.

HeLa cells were grown in Dulbecco's modified Eagle's medium (DMEM) containing 10% fetal bovine serum, antibiotics and glutamine. siRNA duplexes were resuspended in 1× siRNA Universal buffer (Dharmacon, Inc.) to 20 μM prior to transfection. HeLa cells in 12-well plates were transfected twice with 4 μl of 20 μM siRNA duplex in 3 μl Lipofectamine 2000 reagent (Invitrogen, Carlsbad, Calif., USA) at 24-hour intervals. For the transfections in which 2 or 3 siRNA duplexes were included, the amount of each duplex was decreased, so that the total amount was the same as in transfections with single siRNAs. Cells were plated into normal culture medium 12 hours prior to experiments, and protein levels were measured 2 or 4 days after the first transfection.

Equal amounts of lysates were resolved by electrophoresis, blotted, and stained with the antibody specific to targeted protein, as well as antibodies specific to unrelated proteins, PP1 phosphatase and Tsg101 (not shown). The cells were lysed in Triton X-100/glycerol solubilization buffer as described previously. Tebar, Bohlander, & Sorkin, Clathrin Assembly Lymphoid Myeloid Leukemia (CALM) Protein: Localization in Endocytic-coated Pits, Interactions with Clathrin, and the Impact of Overexpression on Clathrin-mediated Traffic, Mol. Biol. Cell August 1999, 10:2687. Cell lysates were electrophoresed, transferred to nitrocellulose membranes, and Western blotting was performed with several antibodies followed by detection using enhanced chemiluminescence system (Pierce, Inc). Several x-ray films were analyzed to determine the linear range of the chemiluminescence signals, and the quantifications were performed using densitometry and AlphaImager v5.5 software (Alpha Innotech Corporation). In experiments with Eps15R-targeted siRNAs, cell lysates were subjected to immunoprecipitation with Ab860, and Eps15R was detected in immunoprecipitates by Western blotting as described above.

The antibodies to assess the levels of each protein by Western blot were obtained from the following sources: monoclonal antibody to clathrin heavy chain (TD.1) was obtained from American Type Culture Collection (Rockville, Md., USA); polyclonal antibody to dynamin II was obtained from Affinity Bioreagents, Inc. (Golden, Colo., USA); monoclonal antibodies to EEA.1 and Rab5a were purchased from BD Transduction Laboratories (Los Angeles, Calif., USA); the monoclonal antibody to Tsg101 was purchased from Santa Cruz Biotechnology, Inc. (Santa Cruz, Calif., USA); the monoclonal antibody to GFP was from ZYMED Laboratories Inc. (South San Francisco, Calif., USA); the rabbit polyclonal antibodies Ab32 specific to α-adaptins and Ab20 to CALM were described previously Sorkin, et al, Stoichiometric Interaction of the Epidermal Growth Factor Receptor with the Clathrin-associated Protein Complex AP-2, J. Biol. Chem. January 1995, 270:619, the polyclonal antibodies to clathrin light chains A and B were kindly provided by Dr. F. Brodsky (UCSF); monoclonal antibodies to PP1 (BD Transduction Laboratories) and α-Actinin (Chemicon) were kindly provided by Dr. M. Dell'Acqua (University of Colorado); Eps15 Ab577 and Eps15R Ab860 were kindly provided by Dr. P. P. Di Fiore (European Cancer Institute).

FIG. 11 demonstrates the in vivo functionality of 48 individual siRNAs, selected using Formula VIII (most of them will meet the criteria incorporated by Formula IX as well) targeting 12 genes. Various cell lines were transfected with siRNA duplexes (Dup1-4) or pools of siRNA duplexes (Pool), and the cells were lysed 3 days after transfection with the exception of CALM (2 days) and β2 (4 days).

Note a β1-adaptin band (part of AP-1 Golgi adaptor complex) that runs slightly slower than β2 adaptin. CALM has two splice variants, 66 and 72 kD. The full-length Eps15R (a doublet of ˜130 kD) and several truncated spliced forms of ˜100 kD and ˜70 kD were detected in Eps15R immunoprecipitates (shown by arrows). The cells were lysed 3 days after transfection. Equal amounts of lysates were resolved by electrophoresis and blotted with the antibody specific to a targeted protein (GFP antibody for YFP fusion proteins) and the antibody specific to unrelated proteins PP1 phosphatase or α-actinin, and TSG101. The amount of protein in each specific band was normalized to the amount of non-specific proteins in each lane of the gel. Nearly all of them appear to be functional, which establishes that Formula VIII and IX can be used to predict siRNAs' functionality in general in a genome wide manner.

To generate the fusion of yellow fluorescent protein (YFP) with Rab5b or Rab5c (YFP-Rab5b or YFP-Rab5c), a DNA fragment encoding the full-length human Rab5b or Rab5c was obtained by PCR using Pfu polymerase (Stratagene) with a SacI restriction site introduced into the 5′ end and a KpnI site into the 3′ end and cloned into pEYFP-C1 vector (CLONTECH, Palo Alto, Calif., USA). GFP-CALM and YFP-Rab5a were described previously Tebar, Bohlander, & Sorkin, Clathrin Assembly Lymphoid Myeloid Leukemia (CALM) Protein: Localization in Endocytic-coated Pits, Interactions with Clathrin, and the Impact of Overexpression on Clathrin-mediated Traffic, Mol. Biol. Cell August 1999, 10:2687.

Example IV Validation of the Algorithm Using Eg5, GADPH, ATE1, MEK2, MEK1, QB, LaminA/C, c-myc, Human Cyclophilin, and Mouse Cyclophilin

A number of genes have been identified as playing potentially important roles in disease etiology. Expression profiles of normal and diseased kidneys has implicated Edg5 in immunoglobulin A neuropathy, a common renal glomerular disease. Myc1, MEK1/2 and other related kinases have been associated with one or more cancers, while lamins have been implicated in muscular dystrophy and other diseases. For these reasons, siRNA directed against the genes encoding these classes of molecules would be important research and therapeutic tools.

FIG. 12 illustrates four siRNAs targeting 10 different genes (Table V for sequence and accession number information) that were selected according to the Formula VIII and assayed as individuals and pools in HEK293 cells. The level of siRNA induced silencing was measured using the B-DNA assay. These studies demonstrated that thirty-six out of the forty individual SMART-selected siRNA tested are functional (90%) and all 10 pools are fully functional.

Example V Validation of the Algorithm Using Bcl2

Bcl-2 is a ˜25 kD, 205-239 amino acid, anti-apoptotic protein that contains considerable homology with other members of the BCL family including BCLX, MCL1, BAX, BAD, and BIK. The protein exists in at least two forms (Bcl2a, which has a hydrophobic tail for membrane anchorage, and Bcl2b, which lacks the hydrophobic tail) and is predominantly localized to the mitochondrial membrane. While Bcl2 expression is widely distributed, particular interest has focused on the expression of this molecule in B and T cells. Bcl2 expression is down-regulated in normal germinal center B cells yet in a high percentage of follicular lymphomas, Bcl2 expression has been observed to be elevated. Cytological studies have identified a common translocation ((14;18)(q32;q32)) amongst a high percentage (>70%) of these lymphomas. This genetic lesion places the Bcl2 gene in juxtaposition to immunoglobulin heavy chain gene (IgH) encoding sequences and is believed to enforce inappropriate levels of gene expression, and resistance to programmed cell death in the follicle center B cells. In other cases, hypomethylation of the Bcl2 promoter leads to enhanced expression and again, inhibition of apoptosis. In addition to cancer, dysregulated expression of Bcl-2 has been correlated with multiple sclerosis and various neurological diseases.

The correlation between Bcl-2 translocation and cancer makes this gene an attractive target for RNAi. Identification of siRNA directed against the bcl2 transcript (or Bcl2-IgH fusions) would further our understanding Bcl2 gene function and possibly provide a future therapeutic agent to battle diseases that result from altered expression or function of this gene.

In Silico Identification of Functional siRNA.

To identify functional and hyperfunctional siRNA against the Bcl2 gene, the sequence for Bcl-2 was downloaded from the NCBI Unigene database and analyzed using the Formula VIII algorithm. As a result of these procedures, both the sequence and SMARTscores™ of the Bcl2 siRNA were obtained and ranked according to their functionality. Subsequently, these sequences were BLAST'ed (database) to insure that the selected sequences were specific and contained minimal overlap with unrealated genes. The SMARTscores™ for the top 10 Bcl-2 siRNA are identified in FIG. 13.

In Vivo Testing of Bcl-2 SiRNA

Bcl-2 siRNAs having the top ten SMARTscores™ were selected and tested in a functional assay to determine silencing efficiency. To accomplish this, each of the ten duplexes were synthesized using 2′-O-ACE chemistry and transfected at 100 nM concentrations into cells. Twenty-four hours later assays were performed on cell extracts to assess the degree of target silencing. Controls used in these experiments included mock transfected cells, and cells that were transfected with a non-specific siRNA duplex.

The results of these experiments are presented below (and in FIG. 14) and show that all ten of the selected siRNA induce 80% or better silencing of the Bcl2 message at 100 nM concentrations. These data verify that the algorithm successfully identified functional Bcl2 siRNA and provide a set of functional agents that can be used in experimental and therapeutic environments. siRNA 1 GGGAGAUAGUGAUGAAGUA SEQ. ID NO. 301 siRNA 2 GAAGUACAUCCAUUAUAAG SEQ. ID NO. 302 siRNA 3 GUACGACAACCGGGAGAUA SEQ. ID NO. 303 siRNA 4 AGAUAGUGAUGAAGUACAU SEQ. ID NO. 304 siRNA 5 UGAAGACUCUGCUCAGUUU SEQ. ID NO. 305 siRNA 6 GCAUGCGGCCUCUGUUUGA SEQ. ID NO. 306 siRNA 7 UGCGGCCUCUGUUUGAUUU SEQ. ID NO. 307 siRNA 8 GAGAUAGUGAUGAAGUACA SEQ. ID NO. 308 siRNA 9 GGAGAUAGUGAUGAAGUAC SEQ. ID NO. 309 siRNA 10 GAAGACUCUGCUCAGUUUG SEQ. ID NO. 310

Bcl2 siRNA: Sense Strand, 5′→3′

Example VI Sequences Selected by the Algorithm

Sequences of the siRNAs selected using Formulas (Algorithms) VIII and IX with their corresponding ranking, which have been evaluated for the silencing activity in vivo in the present study (Formula VIII and IX, respectively) are shown in Table V. It should be noted that the “t” residues in Table V, and elsewhere, when referring to siRNA, should be replaced by “u” residues. TABLE V Gene Accession Formula Formula Name Number SEQ. ID NO. FTllSeqTence VIII IX CLTC NM_004859 SEQ. ID NO. 2400 GAAAGAATCTGTAGAGAAA 76 94.2 CLTC NM_004859 SEQ. ID NO. 2401 GCAATGAGCTGTTTGAAGA 65 39.9 CLTC NM_004859 SEQ. ID NO. 2402 TGACAAAGGTGGATAAATT 57 38.2 CLTC NM_004859 SEQ. ID NO. 2403 GGAAATGGATCTCTTTGAA 54 49.4 CLTA NM_001833 SEQ. ID NO. 2404 GGAAAGTAATGGTCCAACA 22 55.5 CLTA NM_001833 SEQ. ID NO. 2405 AGACAGTTATGCAGCTATT 4 22.9 CLTA NM_001833 SEQ. ID NO. 2406 CCAATTCTCGGAAGCAAGA 1 17 CLTA NM_001833 SEQ. ID NO. 2407 GAAAGTAATGGTCCAACAG −1 −13 CLTB NM_001834 SEQ. ID NO. 2408 GCGCCAGAGTGAACAAGTA 17 57.5 CLTB NM_001834 SEQ. ID NO. 2409 GAAGGTGGCCCAGCTATGT 15 −8.6 CLTB NM_001834 SEQ. ID NO. 0311 GGAACCAGCGCCAGAGTGA 13 40.5 CLTB NM_001834 SEQ. ID NO. 0312 GAGCGAGATTGCAGGCATA 20 61.7 CALM U45976 SEQ. ID NO. 0313 GTTAGTATCTGATGACTTG 36 −34.6 CALM U45976 SEQ. ID NO. 0314 GAAATGGAACCACTAAGAA 33 46.1 CALM U45976 SEQ. ID NO. 0315 GGAAATGGAACCACTAAGA 30 61.2 CALM U45976 SEQ. ID NO. 0316 CAACTACACTTTCCAATGC 28 6.8 EPS15 NM_001981 SEQ. ID NO. 0317 CCACCAAGATTTCATGATA 48 25.2 EPS15 NM_001981 SEQ. ID NO. 0318 GATCGGAACTCCAACAAGA 43 49.3 EPS15 NM_001981 SEQ. ID NO. 0319 AAACGGAGCTACAGATTAT 39 11.5 EPS15 NM_001981 SEQ. ID NO. 0320 CCACACAGCATTCTTGTAA 33 −23.6 EPS15R NM_021235 SEQ. ID NO. 0321 GAAGTTACCTTGAGCAATC 48 33 EPS15R NM_021235 SEQ. ID NO. 0322 GGACTTGGCCGATCCAGAA 27 33 EPS15R NM_021235 SEQ. ID NO. 0323 GCACTTGGATCGAGATGAG 20 1.3 EPS15R NM_021235 SEQ. ID NO. 0324 CAAAGACCAATTCGCGTTA 17 27.7 DNM2 NM_004945 SEQ. ID NO. 0325 CCGAATCAATCGCATCTTC 6 −29.6 DNM2 NM_004945 SEQ. ID NO. 0326 GACATGATCCTGCAGTTCA 5 −14 DNM2 NM_004945 SEQ. ID NO. 0327 GAGCGAATCGTCACCACTT 5 24 DNM2 NM_004945 SEQ. ID NO. 0328 CCTCCGAGCTGGCGTCTAC −4 −63.6 ARF6 AF93885 SEQ. ID NO. 0329 TCACATGGTTAACCTCTAA 27 −21.1 ARF6 AF93885 SEQ. ID NO. 0330 GATGAGGGACGCCATAATC 7 −38.4 ARF6 AF93885 SEQ. ID NO. 0331 CCTCTAACTACAAATCTTA 4 16.9 ARF6 AF93885 SEQ. ID NO. 0332 GGAAGGTGCTATCCAAAAT 4 11.5 RAB5A BC001267 SEQ. ID NO. 0333 GCAAGCAAGTCCTAACATT 40 25.1 RAB5A BC001267 SEQ. ID NO. 0334 GGAAGAGGAGTAGACCTTA 17 50.1 RAB5A BC001267 SEQ. ID NO. 0335 AGGAATCAGTGTTGTAGTA 16 11.5 RAB5A BC001267 SEQ. ID NO. 0336 GAAGAGGAGTAGACCTTAC 12 7 RAB5B NM_002868 SEQ. ID NO. 0337 GAAAGTCAAGCCTGGTATT 14 18.1 RAB5B NM_002868 SEQ. ID NO. 0338 AAAGTCAAGCCTGGTATTA 6 −17.8 RAB5B NM_002868 SEQ. ID NO. 0339 GGTATGAACGTGAATGATC 3 −21.1 RAB5B NM_002868 SEQ. ID NO. 0340 CAAGCCTGGTATTACGTTT −7 −37.5 RAB5C AF141304 SEQ. ID NO. 0341 GGAACAAGATCTGTCAATT 38 51.9 RAB5C AF141304 SEQ. ID NO. 0342 GCAATGAACGTGAACGAAA 29 43.7 RAB5C AF141304 SEQ. ID NO. 0343 CAATGAACGTGAACGAAAT 18 43.3 RAB5C AF141304 SEQ. ID NO. 0344 GGACAGGAGCGGTATCACA 6 18.2 EEA1 XM_018197 SEQ. ID NO. 0345 AGACAGAGCTTGAGAATAA 67 64.1 EEA1 XM_018197 SEQ. ID NO. 0346 GAGAAGATCTTTATGCAAA 60 48.7 EEA1 XM_018197 SEQ. ID NO. 0347 GAAGAGAAATCAGCAGATA 58 45.7 EEA1 XM_018197 SEQ. ID NO. 0348 GCAAGTAACTCAACTAACA 56 72.3 AP2B1 NM_001282 SEQ. ID NO. 0349 GAGCTAATCTGCCACATTG 49 −12.4 AP2B1 NM_001282 SEQ. ID NO. 0350 GCAGATGAGTTACTAGAAA 44 48.9 AP2B1 NM_001282 SEQ. ID NO. 0351 CAACTTAATTGTCCAGAAA 41 28.2 AP2B1 NM_001282 SEQ. ID NO. 0352 CAACACAGGATTCTGATAA 33 −5.8 PLK NM_005030 SEQ. ID NO. 0353 AGATTGTGCCTAAGTCTCT −35 −3.4 PLK NM_005030 SEQ. ID NO. 0354 ATGAAGATCTGGAGGTGAA 0 −4.3 PLK NM_005030 SEQ. ID NO. 0355 TTTGAGACTTCTTGCCTAA −5 −27.7 PLK NM_005030 SEQ. ID NO. 0356 AGATCACCCTCCTTAAATA 15 72.3 GAPDH NM_002046 SEQ. ID NO. 0357 CAACGGATTTGGTCGTATT 27 −2.8 GAPDH NM_002046 SEQ. ID NO. 0358 GAAATCCCATCACCATCTT 24 3.9 GAPDH NM_002046 SEQ. ID NO. 0359 GACCTCAACTACATGGTTT 22 −22.9 GAPDH NM_002046 SEQ. ID NO. 0360 TGGTTTACATGTTCCAATA 9 9.8 c-Myc SEQ. ID NO. 0361 GAAGAAATCGATGTTGTTT 31 −11.7 c-Myc SEQ. ID NO. 0362 ACACAAACTTGAAGAGCTA 22 51.3 c-Myc SEQ. ID NO. 0363 GGAAGAAATCGATGTTGTT 18 26 c-Myc SEQ. ID NO. 0364 GAAACGACGAGAACAGTTG 18 −8.9 MAP2K1 NM_002755 SEQ. ID NO. 0365 GCACATGGATGGAGGTTCT 26 16 MAP2K1 NM_002755 SEQ. ID NO. 0366 GCAGAGAGAGCAGATTTGA 16 0.4 MAP2K1 NM_002755 SEQ. ID NO. 0367 GAGGTTCTCTGGATCAAGT 14 15.5 MAP2K1 NM_002755 SEQ. ID NO. 0368 GAGCAGATTTGAAGCAACT 14 18.5 MAP2K2 NM_030662 SEQ. ID NO. 0369 CAAAGACGATGACTTCGAA 37 26.4 MAP2K2 NM_030662 SEQ. ID NO. 0370 GATCAGCATTTGCATGGAA 24 −0.7 MAP2K2 NM_030662 SEQ. ID NO. 0371 TCCAGGAGTTTGTCAATAA 17 −4.5 MAP2K2 NM_030662 SEQ. ID NO. 0372 GGAAGCTGATCCACCTTGA 16 59.2 KNSL1(EG5) NM_004523 SEQ. ID NO. 0373 GCAGAAATCTAAGGATATA 53 35.8 KNSL1(EG5) NM_004523 SEQ. ID NO. 0374 CAACAAGGATGAAGTCTAT 50 18.3 KNSL1(EGS) NM_004523 SEQ. ID NO. 0375 CAGCAGAAATCTAAGGATA 41 32.7 KNSL1(EG5) NM_004523 SEQ. ID NO. 0376 CTAGATGGCTTTCTCAGTA 39 3.9 CyclophilinA_ NM_021130 SEQ. ID NO. 0377 AGACAAGGTCCCAAAGACA −16 58.1 CyclophilinA_ NM_021130 SEQ. ID NO. 0378 GGAATGGCAAGACCAGCAA −6 36 CyclophilinA_ NM_021130 SEQ. ID NO. 0379 AGAATTATTCCAGGGTTTA −3 16.1 CyclophilinA_ NM_021130 SEQ. ID NO. 0380 GCAGACAAGGTCCCAAAGA 8 8.9 LAMIN A/C NM_170707 SEQ. ID NO. 0381 AGAAGCAGCTTCAGGATGA 31 38.8 LAMIN A/C NM_170707 SEQ. ID NO. 0382 GAGCTTGACTTCCAGAAGA 33 22.4 LAMIN A/C NM_170707 SEQ. ID NO. 0383 CCACCGAAGTTCACCCTAA 21 27.5 LAMIN A/C NM_170707 SEQ. ID NO. 0384 GAGAAGAGCTCCTCCATCA 55 30.1 CyclophilinB M60857 SEQ. ID NO. 0385 GAAAGAGCATCTACGGTGA 41 83.9 CyclophilinB M60857 SEQ. ID NO. 0386 GAAAGGATTTGGCTACAAA 53 59.1 CyclophilinB M60857 SEQ. ID NO. 0387 ACAGCAAATTCCATCGTGT −20 28.8 CyclophilinB M60857 SEQ. ID NO. 0388 GGAAAGACTGTTCCAAAAA 2 27 DBI1 NM_020548 SEQ. ID NO. 0389 CAACACGCCTCATCCTCTA 27 −7.6 DBI2 NM_020548 SEQ. ID NO. 0390 CATGAAAGCTTACATCAAC 25 −30.8 DBI3 NM_020548 SEQ. ID NO. 0391 AAGATGCCATGAAAGCTTA 17 22 DBI4 NM_020548 SEQ. ID NO. 0392 GCACATACCGCCTGAGTCT 15 3.9 rLUC1 SEQ. ID NO. 0393 GATCAAATCTGAAGAAGGA 57 49.2 rLUC2 SEQ. ID NO. 0394 GCCAAGAAGTTTCCTAATA 50 13.7 rLUC3 SEQ. ID NO. 0395 CAGCATATCTTGAACCATT 41 −2.2 rLUC4 SEQ. ID NO. 0396 GAACAAAGGAAACGGATGA 39 29.2 SeAP1 NM_031313 SEQ. ID NO. 0397 CGGAAACGGTCCAGGCTAT 6 26.9 SeAP2 NM_031313 SEQ. ID NO. 0398 GCTTCGAGCAGACATGATA 4 −11.2 SeAP3 NM_031313 SEQ. ID NO. 0399 CCTACACGGTCCTCCTATA 4 4.9 SeAP4 NM_031313 SEQ. ID NO. 0400 GCCAAGAACCTCATCATCT 1 −9.9 fLUC1 SEQ. ID NO. 0401 GATATGGGCTGAATACAAA 54 40.4 fLUC2 SEQ. ID NO. 0402 GCACTCTGATTGACAAATA 47 54.7 fLUC3 SEQ. ID NO. 0403 TGAAGTCTCTGATTAAGTA 46 34.5 fLUC4 SEQ. ID NO. 0404 TCAGAGAGATCCTCATAAA 40 11.4 mCyclo_1 NM_008907 SEQ. ID NO. 0405 GCAAGAAGATCACCATTTC 52 46.4 mCyclo_2 NM_008907 SEQ. ID NO. 0406 GAGAGAAATTTGAGGATGA 36 70.7 mCyclo_3 NM_008907 SEQ. ID NO. 0407 GAAAGGATTTGGCTATAAG 35 −1.5 mCyclo_4 NM_008907 SEQ. ID NO. 0408 GAAAGAAGGCATGAACATT 27 10.3 BCL2_1 NM_000633 SEQ. ID NO. 0409 GGGAGATAGTGATGAAGTA 21 72 BCL2_2 NM_000633 SEQ. ID NO. 0410 GAAGTACATCCATTATAAG 1 3.3 BCL2_3 NM_000633 SEQ. ID NO. 0411 GTACGACAACCGGGAGATA 1 35.9 BCL2_4 NM_000633 SEQ. ID NO. 0412 AGATAGTGATGAAGTACAT −12 22.1 BCL2_5 NM_000633 SEQ. ID NO. 0413 TGAAGACTCTGCTCAGTTT 36 19.1 BCL2_6 NM_000633 SEQ. ID NO. 0414 GCATGCGGCCTCTGTTTGA 5 −9.7 QB1 NM_003365.1 SEQ. ID NO. 0415 GCACACAGCUUACUACAUC 52 −4.8 QB2 NM_003365.1 SEQ. ID NO. 0416 GAAAUGCCCUGGUAUCUCA 49 22.1 QB3 NM_003365.1 SEQ. ID NO. 0417 GAAGGAACGUGAUGUGAUC 34 22.9 QB4 NM_003365.1 SEQ. ID NO. 0418 GCACUACUCCUGUGUGUGA 28 20.4 ATE1-1 NM_007041 SEQ. ID NO. 0419 GAACCGAGCUGGAGAACUU 45 15.5 ATE1-2 NM_007041 SEQ. ID NO. 0420 GAUAUACAGUGUGAUCUUA 40 12.2 ATE1-3 NM_007041 SEQ. ID NO. 0421 GUACUACGAUCCUGAUUAU 37 32.9 ATE1-4 NM_007041 SEQ. ID NO. 0422 GUGCCGACCUUUACAAUUU 35 18.2 EGFR-1 NM_005228 SEQ. ID NO. 0423 GAAGGAAACTGAATTCAAA 68 79.4 EGFR-1 NM_005228 SEQ. ID NO. 0424 GGAAATATGTACTACGAAA 49 49.5 EGFR-1 NM_005228 SEQ. ID NO. 0425 CCACAAAGCAGTGAATTTA 41 7.6 EGFR-1 NM 005228 SEQ. ID NO. 0426 GTAACAAGCTCACGCAGTT 40 25.9

Example VII Genome-Wide Application of Formula VIII or Formula X

The examples described above demonstrate that the algorithm(s) can successfully identify functional siRNA and that these duplexes can be used to induce the desirable phenotype of transcriptional knockdown or knockout. Each gene or family of genes in each organism plays an important role in maintaining physiological homeostasis and the algorithm can be used to develop functional, highly functional, or hyperfunctional siRNA to each gene. In one example of how this is accomplished, the entire online ncbi refseq, locuslink, and/or unigene database for the human genome is first downloaded to local servers. Concommitantly, the most current version of the BLAST algorithm/program is also downloaded to enable analysis of all siRNA identified by the algorithm. Prior to applying the algorithm, sequences are filtered to eliminate all non-coding sequences (e.g., 3′ and 5′ UTRs) and sequences that contain single nucleotide polymorphisms (SNPs). In addition, in one version of the siRNA selection process, only those sequences that are associated with all isoforms (e.g., splice variants) of a given gene are reserved and considered for targeting. Subsequently, a list of all potential siRNAs (including a 19 basepair “core” sequence with two basepair 3′ overhangs) is generated for each gene sequence. This group is then filtered to eliminate sequences that contain any one of a number of undesirable traits including, but not limited to: 1) sequences that contain more than two GC basepairs in the last 5 nucleotides of the 3′ end of the sense strand, and 2) sequences that contained internal repeats that could potentially form hairpin structures. The output of these procedures are then submitted for scoring by the algorithm. In this example, the pre-filtered database was processed with Formula VIII or Formula X and the top 5-100 siRNAs having scores of 75 (adjusted) or greater were selected. If desired, the sequences of these siRNA can be BLAST'ed against the Unigene database containing all sequences in the genome of choice (e.g., the human genome) to eliminate any duplexes that show undesirable degrees of homology to sequences other than the intended target. The sequences of the (roughly) top 100 sequences for each gene are provided on the enclosed CDs in electronic form. In this example, the Formula X sequences were first generated using the procedures described above and subsequently compared to Formula VIII generated sequences. Formula VIII sequences that were also identified by Formula X were then removed (subtracted) from this database (Table XIII) to eliminate duplications.

With respect to the material on disk which is part of this disclosure, there are two tables provided in text format. Table XII, which is located in a file entitled table-xii.txt, created 26 Apr. 2004, with a file size of 110,486 kb, provides a list of the 5-100 sequences for each target, identified by Formula VIII as having the highest relative SMARTscores™ for the target analyzed. Table XIII, which is located in a file entitled table-xiii.txt, created 26 Apr. 2004, with a file size of 23,146 kb, provides a list of the 5-100 sequences for each target identified by Formula X. In addition, each table provides information concerning: the gene name, an NCBI accession number, an adjusted SMARTscore, and a sequence ID number. Any of the provided sequences can be used for gene silencing either alone or in combination with other sequences. The information contained on the disks is part of this patent application and is incorporated into the specification by reference. One may use these tables in order to identify functional siRNAs for the gene provided therein, by simply looking for the gene of interest and an siRNA that is listed as functional. Preferably, one would select one or more of the siRNAs that is most optimized for the target of interest and is denoted as a pool pick.

Table XII: siRNA Selected by Formula VIII

See data submitted herewith on a CD-ROM in accordance with PCT Administrative Instructions Part 8. Table XII is included on the compact disk labeled COPY 1—TABLES PART DISK 1/1, TABLES XII and XIII (provided in triplicate, which copies are identical), in a file entitled table-xii.txt, date of creation 26 Apr. 2004, with a size of 110,486 kb.

Table XIII: siRNA Selected by Formula X

See data submitted herewith on a CD-ROM in accordance with PCT Administrative Instructions Part 8. Table XIII is included on the compact disk labeled COPY 1—TABLES PART DISK 1/1, TABLES XII and XIII (provided in triplicate, which copies are identical), in file entitled table-xiii.txt, date of creation 26 Apr. 2004, with a size of 23,146 kb.

Many of the genes to which the described siRNA are directed play critical roles in disease etiology. For this reason, the siRNAs listed in the accompanying compact disk may potentially act as therapeutic agents. A number of prophetic examples follow and should be understood in view of the siRNA that are identified on the accompanying CD. To isolate these siRNAs, the appropriate message sequence for each gene is analyzed using one of the before mentioned formulas (preferably formula VIII) to identify potential siRNA targets. Subsequently these targets are BLAST'ed to eliminate homology with potential off-targets.

The list of potential disease targets is extensive. For instance, over-expression of Bcl10 has been implicated in the development of MALT lymphoma (mucosa associated lymphoid tissue lymphoma) and thus, functional, highly functional, or hyperfunctional siRNA directed against that gene (e.g., SEQ. ID NO. 0427: GGAAACCUCUCAUUGCUAA; SEQ. ID NO. 0428: GAAAGAACCUUGCCGAUCA; SEQ. ID NO. 0429: GGAAAUACAUCAGAGCUUA, or SEQ. ID NO. 0430: GAAAGUAUGUGUCUUAAGU) may contribute to treatment of this disorder.

In another example, studies have shown that molecules that inhibit glutamine:fructose-6-phosphate aminotransferase (GFA) may act to limit the symptoms suffered by Type II diabetics. Thus, functional, highly functional, or hyperfunctional siRNA directed against GFA (also known as GFPT1: siRNA=SEQ. ID NO. 0433 UGAAACGGCUGCCUGAUUU; SEQ. ID NO. 0434 GAAGUUACCUCUUACAUUU; SEQ. ID NO. 0435 GUACGAAACUGUAUGAUUA; SEQ. ID NO. 0436 GGACGAGGCUAUCAUUAUG) may contribute to treatment of this disorder.

In another example, the von Hippel-Lindau (VHL) tumor suppressor has been observed to be inactivated at a high frequency in sporadic clear cell renal cell carcinoma (RCC) and RCCs associated with VHL disease. The VHL tumor suppressor targets hypoxia-inducible factor-1 alpha (HIF-1 alpha), a transcription factor that can induce vascular endothelial growth factor (VEGF) expression, for ubiquitination and degradation. Inactivation of VHL can lead to increased levels of HIF-1 alpha, and subsequent VEGF over expression. Such over expression of VEGF has been used to explain the increased (and possibly necessary) vascularity observed in RCC. Thus, functional, highly functional, or hyperfunctional siRNAs directed against either HIF-1 alpha (SEQ. ID NO. 0437 GAAGGAACCUGAUGCUUUA; SEQ. ID NO. 0438 GCAUAUAUCUAGAAGGUAU; SEQ. ID NO. 0439 GAACAAAUACAUGGGAUUA; SEQ. ID NO. 0440 GGACACAGAUUUAGACUUG) or VEGF (SEQ. ID NO. 0441 GAACGUACUUGCAGAUGUG; SEQ. ID NO. 0442 GAGAAAGCAUUUGUUUGUA; SEQ. ID NO. 0443 GGAGAAAGCAUUUGUUUGU; SEQ. ID NO. 0444 CGAGGCAGCUUGAGUUAAA) may be useful in the treatment of renal cell carcinoma.

In another example, gene expression of platelet derived growth factor A and B (PDGF-A and PDGF-B) has been observed to be increased 22- and 6-fold, respectively, in renal tissues taken from patients with diabetic nephropathy as compared with controls. These findings suggest that over expression of PDGF A and B may play a role in the development of the progressive fibrosis that characterizes human diabetic kidney disease. Thus, functional, highly functional, or hyperfunctional siRNAs directed against either PDGF A

(SEQ. ID NO. 0445: GGUAAGAUAUUGUGCUUUA;

SEQ. ID NO. 0446: CCGCAAAUAUGCAGAAUUA;

SEQ. ID NO. 0447: GGAUGUACAUGGCGUGUUA;

SEQ. ID NO. 0448: GGUGAAGUUUGUAUGUUUA) or

PDGF B

(SEQ. ID NO. 0449: CCGAGGAGCUUUAUGAGAU;

SEQ. ID NO. 0450: GCUCCGCGCUUUCCGAUUU;

SEQ. ID NO. 0451 GAGCAGGAAUGGUGAGAUG;

SEQ. ID NO. 0452: GAACUUGGGAUAAGAGUGU;

SEQ. ID NO. 0453 CCGAGGAGCUUUAUGAGAU;

SEQ. ID NO. 0454 UUUAUGAGAUGCUGAGUGA) may be useful in the treatment of this form of kidney disorder.

In another example, a strong correlation exists between the over-expression of glucose transporters (e.g., GLUT12) and cancer cells. It is predicted that cells undergoing uncontrolled cell growth up-regulate GLUT molecules so that they can cope with the heightened energy needs associated with increased rates of proliferation and metastasis. Thus, siRNA-based therapies that target the molecules such as GLUT1 (also known as SLC2A1: siRNA=

SEQ. ID NO.: 0455 GCAAUGAUGUCCAGAAGAA;

SEQ. ID NO.: 0456 GAAGAAUAUUCAGGACUUA;

SEQ. ID NO.: 0457 GAAGAGAGUCGGCAGAUGA;

SEQ. ID NO.: 0458 CCAAGAGUGUGCUAAAGAA)

GLUT12 (also known as SLCA12: siRNA=

SEQ. ID NO. 0459: GAGACACUCUGAAAUGAUA;

SEQ. ID NO. 0460: GAAAUGAUGUGGAUAAGAG;

SEQ. ID NO. 0461: GAUCAAAUCCUCCCUGAAA;

SEQ. ID NO. 0462: UGAAUGAGCUGAUGAUUGU) and other related transporters, may be of value in treating a multitude of malignancies.

The siRNA sequences listed above are presented in a 5′→3′ sense strand direction. In addition, siRNA directed against the targets listed above as well as those directed against other targets and listed in the accompanying compact disk may be useful as therapeutic agents.

Example VIII Evidence for the Benefits of Pooling

Evidence for the benefits of pooling have been demonstrated using the reporter gene, luciferase. Ninety siRNA duplexes were synthesized using Dharmacon proprietary ACE® chemistry against one of the standard reporter genes: firefly luciferase. The duplexes were designed to start two base pairs apart and to cover approximately 180 base pairs of the luciferase gene (see sequences in Table III). Subsequently, the siRNA duplexes were co-transfected with a luciferase expression reporter plasmid into HEK293 cells using standard transfection protocols and luciferase activity was assayed at 24 and 48 hours.

Transfection of individual siRNAs showed standard distribution of inhibitory effect. Some duplexes were active, while others were not. FIG. 15 represents a typical screen of ninety siRNA duplexes (SEQ. ID NO. 0032-0120) positioned two base pairs apart. As the figure suggests, the functionality of the siRNA duplex is determined more by a particular sequence of the oligonucleotide than by the relative oligonucleotide position within a gene or excessively sensitive part of the mRNA, which is important for traditional anti-sense technology.

When two continuous oligonucleotides were pooled together, a significant increase in gene silencing activity was observed. (See FIG. 16) A gradual increase in efficacy and the frequency of pools functionality was observed when the number of siRNAs increased to 3 and 4. (FIGS. 16, 17). Further, the relative positioning of the oligonucleotides within a pool did not determine whether a particular pool was functional (see FIG. 18, in which 100% of pools of oligonucleotides distanced by 2, 10 and 20 base pairs were functional).

However, relative positioning may nonetheless have an impact. An increased functionality may exist when the siRNA are positioned continuously head to toe (5′ end of one directly adjacent to the 3′ end of the others).

Additionally, siRNA pools that were tested performed at least as well as the best oligonucleotide in the pool, under the experimental conditions whose results are depicted in FIG. 19. Moreover, when previously identified non-functional and marginally (semi) functional siRNA duplexes were pooled together in groups of five at a time, a significant functional cooperative action was observed. (See FIG. 20) In fact, pools of semi-active oligonucleotides were 5 to 25 times more functional than the most potent oligonucleotide in the pool. Therefore, pooling several siRNA duplexes together does not interfere with the functionality of the most potent siRNAs within a pool, and pooling provides an unexpected significant increase in overall functionality

Example IX Additional Evidence of the Benefits of Pooling

Experiments were performed on the following genes: β-galactosidase, Renilla luciferase, and Secreted alkaline phosphatase, which demonstrates the benefits of pooling. (see FIG. 21). Individual and pools of siRNA (described in Figure legend 21) were transfected into cells and tested for silencing efficiency. Approximately 50% of individual siRNAs designed to silence the above-specified genes were functional, while 100% of the pools that contain the same siRNA duplexes were functional.

Example X Highly Functional siRNA

Pools of five siRNAs in which each two siRNAs overlap to 10-90% resulted in 98% functional entities (>80% silencing). Pools of siRNAs distributed throughout the mRNA that were evenly spaced, covering an approximate 20-2000 base pair range, were also functional. When the pools of siRNA were positioned continuously head to tail relative to mRNA sequences and mimicked the natural products of Dicer cleaved long double stranded RNA, 98% of the pools evidenced highly functional activity (>95% silencing).

Example XI Human Cyclophilin B

Table III above lists the siRNA sequences for the human cyclophilin B protein. A particularly functional siRNA may be selected by applying these sequences to any of Formula I to VII above.

Alternatively, one could pool 2, 3, 4, 5 or more of these sequences to create a kit for silencing a gene. Preferably, within the kit there would be at least one sequence that has a relatively high predicted functionality when any of Formulas I-VII is applied.

Example XII Sample Pools of siRNAs and Their Application to Human Disease

The genetic basis behind human disease is well documented and siRNA may be used as both research or diagnostic tools and therapeutic agents, either individually or in pools. Genes involved in signal transduction, the immune response, apoptosis, DNA repair, cell cycle control, and a variety of other physiological functions have clinical relevance and therapeutic agents that can modulate expression of these genes may alleviate some or all of the associated symptoms. In some instances, these genes can be described as a member of a family or class of genes and siRNA (randomly, conventionally, or rationally designed) can be directed against one or multiple members of the family to induce a desired result.

To identify rationally designed siRNA to each gene, the sequence was analyzed using Formula VIII or Formula X to identify rationally designed siRNA. To confirm the activity of these sequences, the siRNA are introduced into a cell type of choice (e.g., HeLa cells, HEK293 cells) and the levels of the appropriate message are analyzed using one of several art proven techniques. siRNA having heightened levels of potency can be identified by testing each of the before mentioned duplexes at increasingly limiting concentrations. Similarly, siRNA having increased levels of longevity can be identified by introducing each duplex into cells and testing functionality at 24, 48, 72, 96, 120, 144, 168, and 192 hours after transfection. Agents that induce >95% silencing at sub-nanomolar concentrations and/or induce functional levels of silencing for >96 hours are considered hyperfunctional.

Example XIII

The information presented in Tables XII and XIII provides the siRNA sequence (sense strand), the gene name, the NCBI accession number, the adjusted algorithm score, and the sequence ID number. All sequences have an adjusted score of 75 or above. For Table XIII, Formula X derived sequences were compared with Formula VIII sequences. Sequences that were in common with both were eliminated from Table XIII. Pool picks are typically identified as gene specific siRNA that have the hightest adjusted scores.

The following are non-limiting examples of families of proteins to which siRNA described in this document are targeted against:

Transporters, Pumps, and Channels

Transporters, pumps, and channels represent one class of genes that are attractive targets for siRNAs. One major class of transporter molecules are the ATP-binding cassette (ABC) transporters. To date, nearly 50 human ABC-transporter genes have been characterized and have been shown to be involved in a variety of physiological functions including transport of bile salts, nucleosides, chloride ions, cholesterol, toxins, and more. Predominant among this group are MDR1 (which encodes the P-glycoprotein, NP_(—)000918), the MDR-related proteins (MRP1-7), and the breast cancer resistance protein (BCRP). In general, these transporters share a common structure, with each protein containing a pair of ATP-binding domains (also known as nucleotide binding folds, NBF) and two sets of transmembrane (TM) domains, each of which typically contains six membrane-spanning α-helices. The genes encoding this class of transporter are organized as either full transporters (i.e., containing two TM and two NBF domains) or as half transporters that assemble as either homodimers or heterodimers to create functional transporters. As a whole, members of the family are widely dispersed throughout the genome and show a high degree of amino acid sequence identify among eukaryotes.

ABC-transporters have been implicated in several human diseases. For instance, molecular efflux pumps of this type play a major role in the development of drug resistance exhibited by a variety of cancers and pathogenic microorganisms. In the case of human cancers, increased expression of the MDR1 gene and related pumps have been observed to generate drug resistance to a broad collection of commonly used chemotherapeutics including doxorubicin, daunorubicin, vinblastine, vincristine, colchicines. In addition to the contribution these transporters make to the development of multi-drug resistance, there are currently 13 human genetic diseases associated with defects in 14 different transporters. The most common of these conditions include cystic fibrosis, Stargardt disease, age-related macular degeneration, adrenoleukodystrophy, Tangier disease, Dubin-Johnson syndrome and progressive familial intrahepatic cholestasis. For this reason, siRNAs directed against members of this, and related, families are potentially valuable research and therapeutic tools.

With respect to channels, analysis of Drosophila mutants has enabled the initial molecular isolation and characterization of several distinct channels including (but not limited to) potassium (K+) channels. This list includes shaker (Sh), which encodes a voltage activated K⁺ channel, slowpoke (Slo), a Ca²⁺ activated K⁺ channel, and ether-a-go-go (Eag). The Eag family is further divided into three subfamilies: Eag, Elk (eag-like K channels), and Erg (Eag related genes).

The Erg subfamily contains three separate family members (Erg1-3) that are distantly related to the sh family of voltage activated K⁺ channels. Like sh, erg polypetides contain the classic six membrane spanning architecture of K⁺ channels (S1-S6) but differ in that each includes a segment associated with the C-terminal cytoplasmic region that is homologous to cyclic nucleotide binding domains (cNBD). Like many isolated ion channel mutants, erg mutants are temperature-sensitive paralytics, a phenotype caused by spontaneous repetitive firing (hyperactivity) in neurons and enhanced transmitter release at the neuromuscular junction.

Initial studies on the tissue distribution of all three members of the erg subfamily show two general patterns of expression. Erg1 and erg3 are broadly expressed throughout the nervous system and are observed in the heart, the superior mesenteric ganglia, the celiac ganglia, the retina, and the brain. In contrast, erg2 shows a much more restricted pattern of expression and is only observed in celiac ganglia and superior mesenteric ganglia. Similarly, the kinetic properties of the three erg potassium channels are not homogeneous. Erg1 and erg2 channels are relatively slow activating delayed rectifiers whereas the erg3 current activates rapidly and then exhibits a predominantly transient component that decays to a sustained plateau. The current properties of all three channels are sensitive to methanesulfonanilides, suggesting a high degree of conservation in the pore structure of all three proteins.

Recently, the erg family of K⁺ channels has been implicated in human disease. Consistent with the observation that erg1 is expressed in the heart, single strand conformation polymorphism and DNA sequence analyses have identified HERG (human erg1) mutations in six long-QT-syndrome (LQT) families, an inherited disorder that results in sudden death from a ventricular tachyarrythmia. Thus siRNA directed against this group of molecules (e.g., KCNH1-8) will be of extreme therapeutic value.

Another group of channels that are potential targets of siRNAs are the CLCA family that mediate a Ca²⁺-activated Cl⁻ conductance in a variety of tissues. To date, two bovine (bCLC1; bCLCA2 (Lu-ECAM-1)), three mouse (mCLCA1; mCLCA2; mCLCA3) and four human (hCLCA1; hCLCA2; hCLCA3; hCLCA4) CLCA family members have been isolated and patch-clamp studies with transfected human embryonic kidney (HEK-293) cells have shown that bCLCA1, mCLCA1, and hCLCA1 mediate a Ca²⁺-activated Cl⁻ conductance that can be inhibited by the anion channel blocker DIDS and the reducing agent dithiothreitol (DTT).

The protein size, structure, and processing seem to be similar among different CLCA family members and has been studied in greatest detail for Lu-ECAM-1. The Lu-ECAM-1 open reading frame encodes a precursor glycoprotein of 130 kDa that is processed to a 90-kDa amino-terminal cleavage product and a group of 30- to 40-kDa glycoproteins that are glycosylation variants of a single polypeptide derived from its carboxy terminus. Both subunits are associated with the outer cell surface, but only the 90-kDa subunit is thought to be anchored to the cell membrane via four transmembrane domains.

Although the protein processing and function appear to be conserved among CLCA homologs, significant differences exist in their tissue expression patterns. For example, bovine Lu-ECAM-1 is expressed primarily in vascular endothelia, bCLCA1 is exclusively detected in the trachea, and hCLCA1 is selectively expressed in a subset of human intestinal epithelial cells. Thus the emerging picture is that of a multigene family with members that are highly tissue specific, similar to the ClC family of voltage-gated Cl⁻ channels. The human channel, hCLCA2, is particular interesting from a medical and pharmacological standpoint. CLCA2 is expressed on the luminal surface of lung vascular endothelia and serves as an adhesion molecule for lung metastatic cancer cells, thus mediating vascular arrest and lung colonization. Expression of this molecule in normal mammary epithelium is consistently lost in human breast cancer and in nearly all tumorigenic breast cancer cell lines. Moreover, re-expression of hCLCA2 in human breast cancer cells abrogates tumorigenicity in nude mice, implying that hCLCA2 acts as a tumour suppressor in breast cancer. For these reasons, siRNA directed against CLCA family members and related channels may prove to be valuable in research and therapeutic venues.

Transporters Involved in Synaptic Transmission

Synaptic transmission involves the release of a neurotransmitter into the synaptic cleft, interaction of that transmitter with a postsynaptic receptor, and subsequent removal of the transmitter from the cleft. In most synapses the signal is terminated by a rapid reaccumulation of the neurotransmitter into presynaptic terminals. This process is catalyzed by specific neurotransmitter transporters that are often energized by the electrochemical gradient of sodium across the plasma membrane of the presynaptic cells.

Aminobutyric acid (GABA) is the major inhibitory neurotransmitter in the central nervous system. The inhibitory action of GABA, mediated through GABA_(A)/GABA_(B) receptors, and is regulated by GABA transporters (GATs), integral membrane proteins located perisynaptically on neurons and glia. So far four different carriers (GAT1-GAT4) have been cloned and their cellular distribution has been partly worked out. Comparative sequence analysis has revealed that GABA transporters are related to several other proteins involved in neurotransmitter uptake including gamma-aminobutyric acid transporters, monoamine transporters, amino acid transporters, certain “orphan” transporters, and the recently discovered bacterial transporters. Each of these proteins has a similar 12 transmembrane helices topology and relies upon the Na+/Cl− gradient for transport function. Transport rates are dependent on substrate concentrations, with half-maximal effective concentrations for transport frequently occurring in the submicromolar to low micromolar range. In addition, transporter function is bidirectional, and non-vesicular efflux of transmitter may contribute to ambient extracellular transmitter levels.

Recent evidence suggests that GABA transporters, and neurotransmitter transporters in general, are not passive players in regulating neuronal signaling; rather, transporter function can be altered by a variety of initiating factors and signal transduction cascades. In general, this functional regulation occurs in two ways, either by changing the rate of transmitter flux through the transporter or by changing the number of functional transporters on the plasma membrane. A recurring theme in transporter regulation is the rapid redistribution of the transporter protein between intracellular locations and the cell surface. In general, this functional modulation occurs in part through activation of second messengers such as kinases, phosphatases, arachidonic acid, and pH. However, the mechanisms underlying transporter phosphorylation and transporter redistribution have yet to be fully elucidated.

GABA transporters play a pathophysiological role in a number of human diseases including temporal lobe epilepsy and are the targets of pharmacological interventions. Studies in seizure sensitive animals show some (but not all) of the GAT transporters have altered levels of expression at times prior to and post seizure, suggesting this class of transporter may affect epileptogenesis, and that alterations following seizure may be compensatory responses to modulate seizure activity. For these reasons, siRNAs directed against members of this family of genes (including but not limited to SLCG6A1-12) may prove to be valuable research and therapeutic tools.

Organic Ion Transporters

The human body is continuously exposed to a great variety of xenobiotics, via food, drugs, occupation, and environment. Excretory organs such as kidney, liver, and intestine defend the body against the potentially harmful effects of these compounds by transforming them into less active metabolites that are subsequently secreted from the system.

Carrier-mediated transport of xenobiotics and their metabolites exist for the active secretion of organic anions and cations. Both systems are characterized by a high clearance capacity and tremendous diversity of substances accepted, properties that result from the existance of multiple transporters with overlapping substrate specificities. The class of organic anion transporters plays a critical role in the elimination of a large number of drugs (e.g., antibiotics, chemotherapeutics, diuretics, nonsteroidal anti-inflammatory drugs, radiocontrast agents, cytostatics); drug metabolites (especially conjugation products with glutathione, glucuronide, glycine, sulfate, acetate); and toxicants and their metabolites (e.g., mycotoxins, herbicides, plasticizers, glutathione S-conjugates of polyhaloalkanes, polyhaloalkenes, hydroquinones, aminophenols), many of which are specifically harmful to the kidney.

Over the past couple of years the number of identified anion transporting molecules has grown tremendously. Uptake of organic anions (OA⁻) across the basolateral membrane is mediated by the classic sodium-dependent organic anion transport system, which includes α-ketoglutarate (α-KG²⁻)/OA⁻ exchange via the organic anion transporter (OAT1) and sodium-ketoglutarate cotransport via the Na⁺/dicarboxylate cotransporter (SDCT2). The organic anion transporting polypetide, Oatp1, and the kidney-specific OAT-K1 and OAT-K2 are seen as potential molecules that mediate facilitated OA⁻ efflux but could also be involved in reabsorption via an exchange mechanism. Lastly the PEPT1 and PEPT2 mediate luminal uptake of peptide drugs, whereas CNT1 and CNT2 are involved in reabsorption of nucleosides.

The organic anion-transporting polypeptide 1 (Oatp1) is a Na⁺- and ATP-independent transporter originally cloned from rat liver. The tissue distribution and transport properties of the Oatp1 gene product are complex. Oatp1 is localized to the basolateral membrane of hepatocytes, and is found on the apical membrane of S3 proximal tubules. Studies with transiently transfected cells (e.g., HeLa cells) have indicated that Oatp1 mediates transport of a variety of molecules including taurocholate, estrone-3-sulfate, aldosterone, cortisol, and others. The observed uptake of taurocholate by Oatp1 expressed in X. laevis oocytes is accompanied by efflux of GSH, suggesting that transport by this molecule may be glutathione dependent.

Computer modeling suggests that members of the Oatp family are highly conserved, hydrophobic, and have 12 transmembrane domains. Decreases in expression of Oatp family members have been associated with cholestatic liver diseases and human hepatoblastomas, making this family of proteins of key interest to researchers and the medical community. For these reasons, siRNAs directed against OAT family members (including but not limited to SLC21A2, 3, 6, 8, 9, 11, 12, 14, 15, and related transporters) are potentially useful as research and therapeutic tools.

Nucleoside Transporters

Nucleoside transporters play key roles in physiology and pharmacology. Uptake of exogenous nucleosides is a critical first step of nucleotide synthesis in tissues such as bone marrow and intestinal epithelium and certain parasitic organisms that lack de novo pathways for purine biosynthesis. Nucleoside transporters also control the extracellular concentration of adenosine in the vicinity of its cell surface receptors and regulate processes such as neurotransmission and cardiovascular activity. Adenosine itself is used clinically to treat cardiac arrhythmias, and nucleoside transport inhibitors such as dipyridamole, dilazep, and draflazine function as coronary vasodilators.

In mammals, plasma membrane transport of nucleosides is brought about by members of the concentrative, Na⁺-dependent (CNT) and equilibrative, Na⁺-independent (ENT) nucleoside transporter families. CNTs are expressed in a tissue-specific fashion; ENTs are present in most, possibly all, cell types and are responsible for the movement of hydrophilic nucleosides and nucleoside analogs down their concentration gradients. In addition, structure/function studies of ENT family members have predicted these molecules to contain eleven transmembrane helical segments with an amino terminus that is intracellular and a carboxyl terminus that is extracellular. The proteins have a large glycosylated loop between TMs 1 and 2 and a large cytoplasmic loop between TMs 6 and 7. Recent investigations have implicated the TM 3-6 region as playing a central role in solute recognition. The medical importance of the ENT family of proteins is broad. In humans adenosine exerts a range of cardioprotective effects and inhibitors of ENTs are seen as being valuable in alleviating a variety of cardio/cardiovascular ailments. In addition, responses to nucleoside analog drugs has been observed to vary considerably amongst, e.g., cancer patients. While some forms of drug resistance have been shown to be tied to the up-regulation of ABC-transporters (e.g., MDR1), resistance may also be the result of reduced drug uptake (i.e., reduced ENT expression). Thus, a clearer understanding of ENT transporters may aid in optimizing drug treatments for patients suffering a wide range of malignancies. For these reasons, siRNAs directed against this class of molecules (including SLC28A1-3, SLC29A1-4, and related molecules) may be useful as therapeutic and research tools.

Sulfate Transporters

All cells require inorganic sulfate for normal function. Sulfate is the fourth most abundant anion in human plasma and is the major source of sulfur in many organisms. Sulfation of extracellular matrix proteins is critical for maintaining normal cartilage metabolism and sulfate is an important constituent of myelin membranes found in the brain

Because sulfate is a hydrophilic anion that cannot passively cross the lipid bilayer of cell membranes, all cells require a mechanism for sulfate influx and efflux to ensure an optimal supply. To date, a variety of sulfate transporters have been identified in tissues from many origins. These include the renal sulfate transporters (NaSi-1 and Sat-1), the ubiquitously expressed diastrophic dysplasia sulfate transporter (DTDST), the intestinal sulfate transporter (DRA), and the erythrocyte anion exchanger (AE1). Most, if not all, of these molecules contain the classic 12 transmembrane spanning domain architecture commonly found amongst members of the anion transporter superfamily.

Recently three different sulfate transporters have been associated with specific human genetic diseases. Family members SLC26A2, SLC26A3, and SLC26A4 have been recognized as the disease genes mutated in diastrophic dysplasia, congenital chloride diarrhea (CLD), and Pendred syndrome (PDS), respectively. DTDST is a particularly complex disorder. The gene encoding this molecule maps to chromosome 5q, and encodes two distinct transcripts due to alternative exon usage. In contrast to other sulfate transporters (e.g., Sat-1) anion movement by the DTDST protein is markedly inhibited by either extracellular chloride or bicarbonate. Impaired function of the DTDST gene product leads to undersulfation of proteoglycans and a complex family of recessively inherited osteochondrodysplasias (achondrogenesis type 1B, atelosteogenesis type II, and diastrophic dysplasia) with clinical features including but not limited to, dwarfism, spinal deformation, and specific joint abnormalities. Interestingly, while epidemiological studies have shown that the disease occurs in most populations, it is particularly prevalent in Finland owing to an apparent founder effect. For these reasons, siRNAs directed against this class of genes (including but not limited to SLC26A1-9, and related molecules) may be potentially helpful in both therapeutic and research venues.

Ion Exchangers

Intracellular pH regulatory mechanisms are critical for the maintenance of countless cellular processes. For instance, in muscle cells, contractile processes and metabolic reactions are influenced by pH. During periods of increased energy demands and ischemia, muscle cells produce large amounts of lactic acid that, without quick and efficient disposal, would lead to acidification of the sarcoplasm.

Several different transport mechanisms have evolved to maintain a relatively constant intracellular pH. The relative contribution of each of these processes varies with cell type, the metabolic requirements of the cell, and the local environmental conditions. Intracellular pH regulatory processes that have been characterized functionally include but are not limited to the Na⁺/H⁺ exchange, the Na(HCO₃)_(n) cotransport, and the Na⁺-dependent and -independent Cl⁻/base exchangers. As bicarbonate and CO₂ comprise the major pH buffer of biological fluids, sodium biocarbonate cotransporters (NBCs) are critical. Studies have shown that these molecules exist in numerous tissues including the kidney, brain, liver, cornea, heart, and lung, suggesting that NBCs play an important role in mediating HCO₃ ⁻ transport in both epithelial as well as nonepithelial cells.

Recent molecular cloning experiments have identified the existence of four NBC isoforms (NBC1, 2, 3 and 4) and two NBC-related proteins, AE4 and NCBE (Anion Exchanger 4 and Na-dependent Chloride-Bicarbonate Exchanger). The secondary structure analyses and hydropathy profile of this family predict them to be intrinsic membrane proteins with 12 putative transmembrane domains and several family members exhibit N-linked glycosylation sites, protein kinases A and C, casein kinase II, and ATP/GTP-binding consensus phosphorylation sites, as well as potential sites for myristylation and amidation. AE4 is a relatively recent addition to this family of proteins and shows between 30-48% homology with the other family members. When expressed in COS-7 cells and Xenopus oocytes AE4 exhibits sodium-independent and DIDS-insensitive anion exchanger activity. Exchangers have been shown to be responsible for a variety of human diseases. For instance, mutations in three genes of the anion transporter family (SLC) are believed to cause known hereditary diseases, including chondrodysplasia (SLC26A2, DTD), diarrhea (A3, down-regulated in adenoma/chloride-losing diarrhea protein: DRA/CLD), and goiter/deafness syndrome (A4, pendrin). Moreover, mutations in Na+/HCO3 co-transporters have also been associated with various human maladies. For these reasons, siRNAs directed against these sorts of genes (e.g., SLC4A4-10, and related genes) may be useful for therapeutic and research purposes.

Receptors Involved in Synaptic Transmission

In all vertebrates, fast inhibitory synaptic transmission is the result of the interaction between the neurotransmitters glycine (Gly) and γ-aminobutyric acid (GABA) and their respective receptors. The strychnine-sensitive glycine receptor is especially important in that it acts in the mammalian spinal cord and brain stem and has a well-established role in the regulation of locomotor behavior.

Glycine receptors display significant sequence homology to several other receptors including the nicotinic acetylcholine receptor, the aminobutyric acid receptor type A (GABA_(A)R), and the serotonin receptor type 3 (5-HT₃R) subunits. As members of the superfamily of ligand-gated ion channels, these polypeptides share common topological features. The glycine receptor is composed of two types of glycosylated integral membrane proteins (α1-α4 and β) arranged in a pentameric suprastructure. The alpha subunit encodes a large extracellular, N-terminal domain that carries the structural determinants essential for agonist and antagonist binding, followed by four transmembrane spanning regions (TM1-TM4), with TM2 playing the critical role of forming the inner wall of the chloride channel.

The density, location, and subunit composition of glycine neurotransmitter receptors changes over the course of development. It has been observed that the amount of GlyR gene translation (assessed by the injection of developing rat cerebral cortex mRNA into Xenopus oocytes) decreases with age, whereas that of GABARs increases. In addition, the type and location of mRNAs coding for GlyR changes over the course of development. For instance in a study of the expression of alpha 1 and alpha 2 subunits in the rat, it was observed that (in embryonic periods E11-18) the mantle zone was scarce in the alpha 1 mRNA, but the germinal zone (matrix layer) at E11-14 expressed higher levels of the message. At postnatal day 0 (P0), the alpha 1 signals became manifested throughout the gray matter of the spinal cord. By contrast, the spinal tissues at P0 exhibited the highest levels of alpha 2 mRNA, which decreased with the postnatal development.

In both, man and mouse mutant lines, mutations of GlyR subunit genes result in hereditary motor disorders characterized by exaggerated startle responses and increased muscle tone. Pathological alleles of the Glra1 gene are associated with the murine phenotypes oscillator (spd^(ot)) and spasmodic (spd). Similarly, a mutant allele of Glrb has been found to underly the molecular pathology of the spastic mouse (spa). Resembling the situation in the mouse, a variety of GLRA1 mutant alleles have been shown to be associated with the human neurological disorder hyperekplexia or startle disease. For these reasons, siRNA directed against glycine receptors (GLRA1-3, GLRB, and related molecules), glutamate receptors, GABA receptors, ATP receptors, and related neurotransmitter receptor molecules may be valuable therapeutic and research reagents.

Proteases

Kallikreins

One important class of proteases are the kallikreins, serine endopeptidases that split peptide substrates preferentially on the C-terminal side of internal arginyl and lysyl residues. Kallikreins are generally divided into two distinct groups, plasma kallikreins and tissue kallikreins. Tissue kallikreins represent a large group of enzymes that have substantial similarities at both the gene and protein level. The genes encoding this group are frequently found on a single chromosome, are organized in clusters, and are expressed in a broad range of tissues (e.g., pancreas, ovaries, breast). In contrast, the plasma form of the enzyme is encoded by a single gene (e.g., KLK3) that has been localized to chromosome 4q34-35 in humans. The gene encoding plasma kallikrein is expressed solely in the liver, contains 15 exons, and encodes a glycoprotein that is translated as a preprotein called prekallikrein.

Kallikreins are believed to play an important role in a host of physiological events. For instance, the immediate consequence of plasma prekallikrein activation is the cleavage of high molecular weight kininogen (HK) and the subsequent liberation of bradykinin, a nine amino acid vasoactive peptide that is an important mediator of inflammatory responses. Similarly, plasma kallikrein promotes single-chain urokinase activation and subsequent plasminogen activation, events that are critical to blood coaggulation and wound healing.

Disruptions in the function of kallikreins have been implicated in a variety of pathological processes including imbalances in renal function and inflammatory processes. For these reasons, siRNAs directed against this class of genes (e.g., KLK1-15) may prove valuable in both research and therapeutic settings.

ADAM Proteins

The process of fertilization takes place in a series of discrete steps whereby the sperm interacts with, i) the cumulus cells and the hyaluronic acid extracellular matrix (ECM) in which they are embedded, ii) the egg's own ECM, called the zona pellucida (ZP), and iii) the egg plasma membrane. During the course of these interactions, the “acrosome reaction,” the exocytosis of the acrosome vesicle on the head of the sperm, is induced, allowing the sperm to penetrate the ZP and gain access to the perivitelline space. This process exposes new portions of the sperm membrane, including the inner acrosomal membrane and the equatorial segment, regions of the sperm head that can participate in initial gamete membrane binding.

The interactions of the gamete plasma membranes appear to involve multiple ligands and receptors and are frequently compared to leukocyte-endothelial interactions. These interactions lead to a series of signal transduction events in the egg, known as collectively as egg activation and include the initiation of oscillations in intracellular calcium concentration, the exit from meiosis, the entry into the first embryonic mitosis, and the formation of a block to polyspermy via the release of ZP-modifying enzymes from the egg's cortical granules. Ultimately, sperm and egg not only adhere to each other but also go on to undergo membrane fusion, making one cell (the zygote) from two.

Studies on the process of sperm-egg interactions have identified a number of proteins that are crucial for fertilization. One class of proteins, called the ADAM family (A Disintegrin And Metalloprotease), has been found to be important in spermatogenesis and fertilization, as well as various developmental systems including myogenesis and neurogenesis. Members of the family contain a disintegrin and metalloprotease domain (and therefore have (potentially) both cell adhesion and protease activities), as well as cysteine-rich regions, epidermal growth factor (EGF)-like domains, a transmembrane region, and a cytoplasmic tail. Currently, the ADAM gene family has 29 members and constituents are widely distributed in many tissues including the brain, testis, epididymis, ovary, breast, placenta, liver, heart, lung, bone, and muscle.

One of the best-studied members of the ADAM family is fertilin, a heterodimeric protein comprised of at least two subunits, fertilin alpha and fertilin beta. The fertilin beta gene (ADAM2) has been disrupted with a targeting gene construct corresponding to the exon encoding the fertilin beta disintegrin domain. Sperm from males homozygous for disruptions in this region exhibit defects in multiple facets of sperm function including reduced levels of sperm transit from the uterus to the oviduct, reduced sperm-ZP binding, and reduced sperm-egg binding, all of which contribute to male infertility.

Recently, four new ADAM family members (ADAM 24-27) have been isolated. The deduced amino acid sequences show that all four contain the complete domain organization common to ADAM family members and Northern Blot analysis has shown all four to be specific to the testes. siRNAs directed against this class of genes (e.g., ADAM2 and related proteins) may be useful as research tools and therapeutics directed toward fertility and birth control.

Aminopeptidases

Aminopeptidases are proteases that play critical roles in processes such as protein maturation, protein digestion in its terminal stage, regulation of hormone levels, selective or homeostatic protein turnover, and plasmid stabilization. These enzymes generally have broad substrate specificity, occur in several forms and play a major role in physiological homeostasis. For instance, the effects of bradykinin, angiotensin converting enzyme (ACE), and other vasoactive molecules are muted by one of several peptidases that cleave the molecule at an internal position and eliminate its ability to bind its cognate receptor (e.g., for bradykinin, the B2-receptor).

Among the enzymes that can cleave bradykinin is the membrane bound aminopeptidase P, also referred to as aminoacylproline aminopeptidase, proline aminopeptidase; X-Pro aminopeptidase (eukaryote) and XPNPEP2. Aminopeptidase P is an aminoacylproline aminopeptidase specific for NH₂-terminal Xaa-proline bonds. The enzyme i) is a mono-zinc-containing molecule that lacks any of the typical metal binding motifs found in other zinc metalloproteases, ii) has an active-site configuration similar to that of other members of the MG peptidase family, and iii) is present in a variety of tissues including but not limited to the lung, kidney, brain, and intestine.

Aminopeptidases play an important role in a diverse set of human diseases. Low plasma concentrations of aminopeptidase P are a potential predisposing factor for development of angio-oedema in patients treated with ACE inhibitors, and inhibitors of aminopeptidase P may act as cardioprotectors against other forms of illness including, but not limited to myocardial infarction. For these reasons, siRNAs directed against this family of proteins (including but not limited to XPNPEP1 and related proteins) may be useful as research and therapeutic tools.

Serine Proteases

One important class of proteases are the serine proteases. Serine proteases share a common catalytic triad of three amino acids in their active site (serine (nucleophile), aspartate (electrophile), and histidine (base)) and can hydrolyze either esters or peptide bonds utilizing mechanisms of covalent catalysis and preferential binding of the transition state. Based on the position of their introns serine proteases have been classified into a minimum of four groups including those in which 1) the gene has no introns interrupting the exon coding for the catalytic triad (e.g., the haptoglobin gene,); 2) each gene contains an intron just downstream from the codon for the histidine residue at the active site, a second intron downstream from the exon containing the aspartic acid residue of the active site and a third intron just upstream from the exon containing the serine of the active site (e.g., trypsinogen, chymotrypsinogen, kallikrein and proelastase); 3) the genes contain seven introns interrupting the exons coding the catalytic region (e.g., complement factor B gene); and 4) the genes contain two introns resulting in a large exon that contains both the active site aspartatic acid and serine residues (e.g., factor X, factor IX and protein C genes).

Cytotoxic lymphocytes (e.g., CD8(+) cytotoxic T cells and natural killer cells) form the major defense of higher organisms against virus-infected and transformed cells. A key function of these cells is to detect and eliminate potentially harmful cells by inducing them to undergo apoptosis. This is achieved through two principal pathways, both of which require direct but transient contact between the killer cell and its target. The first pathway involves ligation of TNF receptor-like molecules such as Fas/CD95 to their cognate ligands, and results in mobilization of conventional, programmed cell-death pathways centered on activation of pro-apoptotic caspases. The second mechanism consists of a pathway whereby the toxic contents of a specialized class of secretory vesicles are introduced into the target cell. Studies over the last two decades have identified the toxic components as Granzymes, a family of serine proteases that are expressed exclusively by cytotoxic T lymphocytes and natural killer (NK) cells. These agents are stored in specialized lytic granules and enter the target cell via endocytosis. Like caspases, cysteine proteases that play an important role in apoptosis, granzymes can cleave proteins after acidic residues, especially aspartic acid, and induce apoptosis in the recipient cell.

Granzymes have been grouped into three subfamilies according to substrate specificity. Members of the granzyme family that have enzymatic activity similar to the serine protease chymotrypsin are encoded by a gene cluster termed the ‘chymase locus’. Similarly, granzymes with trypsin-like specificities are encoded by the ‘tryptase locus’, and a third subfamily cleaves after unbranched hydrophobic residues, especially methionine, and are encoded by the ‘Met-ase locus’. All granzymes are synthesized as zymogens and, after clipping of the leader peptide, obtain maximal enzymatic activity subsequent to the removal of an amino-terminal dipeptide.

Granzymes have been found to be important in a number of important biological functions including defense against intracellular pathogens, graft versus host reactions, the susceptibility to transplantable and spontaneous malignancies, lymphoid homeostasis, and the tendency toward auto-immune diseases. For these reasons, siRNAs directed against granszymes (e.g., GZMA, GZMB, GZMH, GZHK, GZMM) and related serine proteases may be useful research and therapeutic reagents.

Kinases

Protein Kinases (PKs) have been implicated in a number of biological processes. Kinase molecules play a central role in modulating cellular physiology and developmental decisions, and have been implicated in a large list of human maladies including cancer, diabetes, and others.

During the course of the last three decades, over a hundred distinct protein kinases have been identified, all with presumed specific cellular functions. A few of these enzymes have been isolated to sufficient purity to perform in vitro studies, but most remain intractable due to the low abundance of these molecules in the cell. To counter this technical difficulty, a number of protein kinases have been isolated by molecular cloning strategies that utilize the conserved sequences of the catalytic domain to isolate closely related homologs. Alternatively, some kinases have been purified (and subsequently studied) based on their interactions with other molecules.

p58 is a member of the p34cdc2-related supergene family and contains a large domain that is highly homologous to the cell division control kinase, cdc2. This new cell division control-related protein kinase was originally identified as a component of semipurified galactosyltransferase; thus, it has been denoted galactosyltransferase-associated protein kinase (GTA-kinase). GTA-kinase has been found to be expressed in both adult and embryonic tissues and is known to phosphorylate a number of substrates, including histone H1, and casein. Interestingly enough, over expression of this molecule in CHO cells has shown that elevated levels of p58 result in a prolonged late telophase and an early G1 phase, thus hinting of an important role for GTA-kinase in cell cycle regulation.

Cyclin Dependent Kinases

The cyclin-dependent kinases (Cdks) are a family of highly conserved serine/threonine kinases that mediate many of the cell cycle transitions that occur during duplication. Each of these Cdk catalytic subunits associates with a specific subset of regulatory subunits, termed cyclins, to produce a distinct Cdk.cyclin kinase complex that, in general, functions to execute a unique cell cycle event.

Activation of the Cdk.cyclin kinases during cellular transitions is controlled by a variety of regulatory mechanisms. For the Cdc2.cyclin B complex, inhibition of kinase activity during S phase and G₂ is accomplished by phosphorylation of two Cdc2 residues, Thr¹⁴ and Tyr¹⁵, which are positioned within the ATP-binding cleft. Phosphorylation of Thr¹⁴ and/or Tyr¹⁵ suppresses the catalytic activity of the molecule by disrupting the orientation of the ATP present within this cleft. In contrast, the abrupt dephosphorylation of these residues by the Cdc25 phosphatase results in the rapid activation of Cdc2.cyclin B kinase activity and subsequent downstream mitotic events. While the exact details of this pathway have yet to be elucidated, it has been proposed that Thr¹⁴/Tyr¹⁵ phosphorylation functions to permit a cell to attain a critical concentration of inactive Cdk.cyclin complexes, which, upon activation, induces a rapid and complete cell cycle transition. Furthermore, there is evidence in mammalian cells that Thr¹⁴/Tyr¹⁵ phosphorylation also functions to delay Cdk activation after DNA damage.

The Schizosaccharomyces pombe wee1 gene product was the first kinase identified that is capable of phosphorylating Tyr¹⁵ in Cdc2. Homologs of the Wee1 kinase have been subsequently identified and biochemically characterized from a wide range of species including human, mouse, frog, Saccharomyces cerevisiae, and Drosophila. In vertebrate systems, where Thr¹⁴ in Cdc2 is also phosphorylated, the Wee1 kinase was capable of phosphorylating Cdc2 on Tyr¹⁵, but not Thr¹⁴, indicating that another kinase was responsible for Thr¹⁴ phosphorylation. This gene, Myt1 kinase, was recently isolated from the membrane fractions of Xenopus egg extracts and has been shown to be capable of phosphorylating Thr¹⁴ and, to a lessor extent, Tyr¹⁵ in Cdc2. A human Myt1 homolog displaying similar properties has been isolated, as well as a non-membrane-associated molecule with Thr¹⁴ kinase activity.

In the past decade it has been shown that cancer can originate from overexpression of positive regulators, such as cyclins, or from underexpression of negative regulators (e.g., p16 (INK4a), p15 (INK4b), p21 (Cip1)). Inhibitors such as Myt1 are the focus of much cancer research because they are capable of controlling cell cycle proliferation, now considered the Holy Grail for cancer treatment. For these reasons, siRNA directed against kinases and kinase inhibitors including but not limited to ABL1, ABL2, ACK1, ALK, AXL, BLK, BMX, BTK, C20orf64, CSF1R, SCK, DDR1, DDR2, DKFZp761P1010, EGFR, EPHA1, EPHA2, EPHA3, EPHA4, EPHA7, EPHA8, EPHB1, EPHB2, EPHB3, EPHB4. EPHB6, ERBB2, ERBB3, ERBB4, FER, FES, FGFR1, FGFR2, FGFR3, FGFR4, FGR, FLT1, FLT3, FLT4, FRK, FYN, HCK, IGF1R, INSR, ITK, JAK1, JAK2, JAK3, KDR, KIAA1079, KIT, LCK, LTK, LYN, MATK, MERTK, MET, MST1R, MUSK, NTRK1, NTRK2, NTRK3, PDGFRA, PDGFRB, PTK2, PTK2B, PTK6, PTK7, PTK9, PTK9L, RET, ROR1, ROR2, ROS1, RYK, SRC, SYK, TEC, TEK, TIE, TNK1, TXK, TYK2, TYRO3, YES 1, and related proteins, may be useful for research and therapeutic purposes.

G Protein Coupled Receptors

One important class of genes to which siRNAs can be directed are G-protein coupled receptors (GPCRs). GPCRs constitute a superfamily of seven transmembrane spanning proteins that respond to a diverse array of sensory and chemical stimuli, such as light, odor, taste, pheromones, hormones and neurotransmitters. GPCRs play a central role in cell proliferation, differentiation, and have been implicated in the etiology of disease.

The mechanism by which G protein-coupled receptors translate extracellular signals into cellular changes was initially envisioned as a simple linear model: activation of the receptor by agonist binding leads to dissociation of the heterotrimeric GTP-binding G protein (Gs, Gi, or Gq) into its alpha and beta/gamma subunits, both of which can activate or inhibit various downstream effector molecules. More specifically, activation of the GPCR induces a conformational change in the Gα subunit, causing GDP to be released and GTP to be bound in its place. The Gα and Gβα subunits then dissociate from the receptor and interact with a variety of effector molecules. For instance in the case of the Gs family, the primary function is to stimulate the intracellular messenger adenylate cyclase (AC), which catalyzes the conversion of cytoplasmic ATP into the secondary messenger cyclic AMP (cAMP). In contrast, the Gi family inhibits this pathway and the Gq family activates phospholipases C (PLC), which cleaves phosphatidylinositol 4,5, bisphosphate (PIP2) to generate inositol-1,4,5-phosphate (IP3) and diacylglycerol (DAG).

More recently, studies have shown that the functions of GPCRs are not limited to their actions on G-proteins and that considerable cross-talk exists between this diverse group of receptor molecules and a second class of membrane bound proteins, the receptor tyrosine kinases (RTKs). A number of GPCRs such as endothelin-1, thrombin, bombesin, and dopamine receptors can activate MAPKs, a downstream effector of the RTK/Ras pathway. Interestingly, the interaction between these two families is not unidirectional and RTKs can also modulate the activity of signaling pathways traditionally thought to be controlled exclusively by ligands that couple to GPCRs. For instance, EGF, which normally activates the MAPK cascade via the EGF receptor can stimulate adenylate cyclase activity by activating Gαs.

There are dozens of members of the G Protein-Coupled Receptor family that have emerged as prominent drug targets in the last decade. One non-limiting list of potential GPCR-siRNA targets is as follows:

CMKLR1

CML1/CMKLR1 (Accession No. Q99788) is a member of the chemokine receptor family of GPCRs that may play a role in a number of diseases including those involved in inflammation and immunological responses (e.g., asthma, arthritis). For this reason, siRNA directed against this protein may prove to be important therapeutic reagents.

Studies of juvenile-onset neuronal ceroid lipofuscinosis (JNCL, Batten disease), the most common form of childhood encephalopathy that is characterized by progressive neural degeneration, show that it is brought on by mutations in a novel lysosomal membrane protein (CLN3). In addition to being implicated in JNCL, CLN3 (GPCR-like protein, Accession No. A57219) expression studies have shown that the CLN3 mRNA and protein are highly over-expressed in a number of cancers (e.g., glioblastomas, neuroblastomas, as well as cancers of the prostate, ovaries, breast, and colon) suggesting a possible contribution of this gene to tumor growth. For this reason, siRNA directed against this protein may prove to be important therapeutic reagents.

CLACR

The calcitonin receptor (CTR/CALCR, Accession No. NM_(—)001742) belongs to “family B” of GPCRs which typically recognized regulatory peptides such as parathyroid hormone, secretin, glucagons and vasoactive intestinal polypeptide. Although the CT receptor typically binds to calcitonin (CT), a 32 amino acid peptide hormone produced primarily by the thyroid, association of the receptor with RAMP (Receptor Activity Modulating Protein) enables it to readily bind other members of the calcitonin peptide family including amylin (AMY) and other CT gene-related peptides (e.g., αCGRP and βCGRP). While the primary function of the calcitonin receptor pertains to regulating osteoclast mediated bone resorption and enhanced Ca⁺² excretion by the kidney, recent studies have shown that CT and CTRs may play an important role in a variety of processes as wide ranging as embryonic/fetal development and sperm function/physiology. In addition, studies have shown that patients with particular CTR genotypes may be at higher risk to lose bone mass and that this GPCR may contribute to the formation of calcium oxalate urinary stones. For this reason, siRNA directed against CTR may be useful as therapeutic reagents.

OXTR

The human oxytocin receptor (OTR, OXTR) is a 389 amino acid polypeptide that exhibits the seven transmembrane domain structure and belongs to the Class-I (rhodopsin-type) family of G-protein coupled receptors. OTR is expressed in a wide variety of tissues throughout development and mediates physiological changes through G(q) proteins and phospholipase C-beta. Studies on the functions of oxytocin and the oxytocin receptor have revealed a broad list of duties. OT and OTR play a role in a host of sexual, maternal and social behaviors that include egg-laying, birth, milk-letdown, feeding, grooming, memory and learning. In addition, it has been hypothesized that abnormalities in the functionality of oxytocin-OTR receptor-ligand system can lead to a host of irregularities including compulsive behavior, eating disorders (such as anorexia), depression, and various forms of neurodegenerative diseases. For these reasons, siRNA directed against this gene (NM_(—)000916) may play an important role in combating OTR-associated illnesses.

EDG GPCRs

Lysophosphatidic acid and other lipid-based hormones/growth factors induce their effects by activating signaling pathways through the G-protein coupled receptors (GPCRs) and have been observed to play important roles in a number of human diseases including cancer, asthma, and vascular pathologies. For instance, during studies of immunoglobulin A nephropathy (IgAN), researchers have observed an enhanced expression of EDG5 (NP_(—)004221) suggesting a contribution of this gene product in the development of IgAN. For that reason, siRNA directed against Edg5 (NM_(—)004230), Edg4 (NM_(—)004720), Edg7 (Nm_(—)012152) and related genes may play an important role in combating human disease.

Genes Involved in Cholesterol Signaling and Biosynthesis

Studies on model genetic organisms such as Drosophila and C. elegans have led to the identification of a plethora of genes that are essential for early development. Mutational analysis and ectopic expression studies have allowed many of these genes to be grouped into discreet signal transduction pathways and have shown that these elements play critical roles in pattern formation and cell differentiation. Disruption of one or more of these genes during early stages of development frequently leads to birth defects whereas as alteration of gene function at later stages in life can result in tumorigenesis.

One critical set of interactions known to exist in both invertebrates and vertebrates is the Sonic Hedgehog-Patched-Gli pathway. Originally documented as a Drosophila segmentation mutant, several labs have recently identified human and mouse orthologs of many of the pathways members and have successfully related disruptions in these genes to known diseases. Pathway activation is initiated with the secretion of Sonic hedgehog. There are three closely related members of the Shh family (Sonic hedgehog, Desert, and Indian) with Shh being the most widely expressed form of the group. The Shh gene product is secreted as a small pro-signal molecule. To successfully initiate its developmental role, Shh is first cleaved, whereupon the N-terminal truncated fragment is covalently modified with cholesterol. The addition of the sterol moiety promotes the interaction between Shh and its cognate membrane bound receptor, Patched (Ptch). There are at least two isoforms of the Patched gene, Ptch1 and Ptch2. Both isoforms contain a sterol-sensing domain (SSD); a roughly 180 amino acid cluster that is found in at least seven different classes of molecules including those involved in cholesterol biosynthesis, vesicular traffic, signal transduction, cholesterol transport, and sterol homeostasis. In the absence of Shh, the Patched protein is a negative regulator of the pathway. In contrast, binding of Shh-cholesterol to the Patched receptor releases the negative inhibition which that molecule enforces on a G-protein coupled receptor known as Smoothened. Subsequent activation of Smoothened (directly or indirectly) leads to the triggering of a trio of transcription factors that belong to the Gli family. All three factors are relatively large, contain a characteristic C2-H2 zinc-finger pentamer, and recognize one of two consensus sequences (SEQ. ID NO. 0463 GACCACCCA or SEQ. ID NO. 0464 GAACCACCCA). In the absence of Shh, Gli proteins are cleaved by the proteosome and the C-terminally truncated fragment translocates to the nucleus and acts as a dominant transcription repressor. In the presence of Shh-cholesterol, Gli repressor formation is inhibited and full-length Gli functions as a transcriptional activator.

Shh and other members of the Shh-PTCH-Gli pathway are expressed in a broad range of tissues (e.g., the notochord, the floorplate of the neural tube, the brain, and the gut) at early stages in development. Not surprisingly, mutations that lead to altered protein expression or function have been shown to induce developmental abnormalities. Defects in the human Shh gene have been shown to cause holoprosencephaly, a midline defect that manifests itself as cleft lip or palate, CNS septation, and a wide range of other phenotypes. Interestingly, defects in cholesterol biosynthesis generate similar Shh-like disorders (e.g., Smith-Lemli-Opitz syndrome) suggesting that cholesterol modification of the Shh gene product is crucial for pathway function. Both the Patched and Smoothened genes have also been shown to be clinically relevant with Smoothened now being recognized as an oncogene that, like PTCH-1 and PTCH-2, is believed to be the causative agent of several forms of adult tumors. For these reasons, siRNA directed against Smoothened (SMO, NM_(—)005631), Patched (PTCH, nm_(—)000264), and additional genes that participate in cholesterol signaling, biosynthesis, and degradation, have potentially useful research and therapeutic applications.

Targeted Pathways.

In addition to targeting siRNA against one or more members of a family of proteins, siRNA can be directed against members of a pathway. Thus, for instance, siRNA can be directed against members of a signal transduction pathway (e.g., the insulin pathway, including AKT1-3, CBL, CBLB, EIF4EBP1, FOXO1A, FOXO3A, FRAP1, GSK3A, GSK3B, IGF1, IGF1R, INPP5D, INSR, IRS1, MLLT7, PDPK1, PIK3CA, PIK3CB, PIK3R1, PIK3R2, PPP2R2B, PTEN, RPS6, RPS6KA1, RPX6KA3, SGK, TSC1, TSC2, AND XPO1), an apoptotic pathway (CASP3,6,7,8,9, DSH1/2, P110, P85, PDK1/2, CATENIN, HSP90, CDC37, P23, BAD, BCLXL, BCL2, SMAC, and others), pathways, involved in DNA damage, cell cycle, and other physiological (p53,MDM2, CHK1/2, BRCA1/2, ATM, ATR, P15INK4, P27, P21, SKP2, CDC25C/A, 14-3-3, PLK, RB, CDK4, GLUT4, Inos, Mtor, FKBP, PPAR, RXR, ER). Similarly, genes involved in immune system function including TNFR1, IL-IR, IRAK1/2, TRAF2, TRAF6, TRADD, FADD, IKKε, IKKγ, IKKβ, IKKα, IkBα, IkBβ, p50, p65, Rac, RhoA, Cdc42, ROCK, Pak1/2/3/4/5/6, cIAP, HDAC1/2, CBP, β-TrCP, Rip2/4, and others are also important targets for the siRNAs described in this document and may be useful in treating immune system disorders. Genes involved in apoptosis, such as Dsh1/2,PTEN, P110 (pan), P85, PDK1/2, Akt1, Akt2, Akt (pan), p70^(S6K), GSK3β, PP2A (cat), β-catenin, HSP90, Cdc37/p50, P23, Bad, BclxL, Bcl2, Smac/Diablo, and Ask1 are potentially useful in the treatment of diseases that involve defects in programmed cell death (e.g., cancer), while siRNA agents directed against p53, MDM2, Chk1/2, BRCA1/2, ATM, ATR, p15^(INK4), P27, P21, Skp2, Cdc25C/A, 14-3-3σ/ε, PLK, Rb, Cdk4, Glut4, iNOS, mTOR, FKBP, PPARγ, RXRα, ERα and related genes may play a critical role in combating diseases associated with disruptions in DNA repair, and cell cycle abnormalities.

Tables VI-Table X below provide examples of useful pools for inhibiting different genes in the human insulin pathway and tyrosine kinase pathways, proteins involved in the cell cycle, the production of nuclear receptors, and other genes. These particular pools are particularly useful in humans, but would be useful in any species that generates an appropriately homologous mRNA. Further, within each of the listed pools any one sequence maybe used independently but preferably at least two of the listed sequences, more preferably at least three, and most preferably all of the listed sequences for a given gene is present. TABLE VI Gene SEQ. Name Acc # GI L.L. Duplex # Sequence ID NO. AKT1 NM_005163 4885060 207 D-003000-05 GACAAGGACGGGCACATTA 465 AKT1 NM_005163 4885060 207 D-003000-06 GGACAAGGACGGGCACATT 466 AKT1 NM_005163 4885060 207 D-003000-07 GCTACTTCCTCCTCAAGAA 467 AKT1 NM_005163 4885060 207 D-003000-08 GACCGCCTCTGCTTTGTCA 468 AKT2 AKT2 NM_001626 6715585 208 D-003001-05 GTACTTCGATGATGAATTT 469 AKT2 NM_001626 6715585 208 D-003001-06 GCAAAGAGGGCATCAGTGA 470 AKT2 NM_001626 6715585 208 D-003001-07 GGGCTAAAGTGACCATGAA 471 AKT2 NM_001626 6715585 208 D-003001-08 GCAGAATGCCAGCTGATGA 472 AKT3 AKT3 NM_005465 32307164 10000 D-003002-05 GGAGTAAACTGGCAAGATG 473 AKT3 NM_005465 32307164 10000 D-003002-06 GACATTAAATTTCCTCGAA 474 AKT3 NM_005465 32307164 10000 D-003002-07 GACCAAAGCCAAACACATT 475 AKT3 NM_005465 32307164 10000 D-003002-08 GAGGAGAGAATGAATTGTA 476 CBL CBL NM_005188 4885116 867 D-003003-05 GGAGACACATTTCGGATTA 477 CBL NM_005188 4885116 867 D-003003-06 GATCTGACCTGCAATGATT 478 CBL NM_005188 4885116 867 D-003003-07 GACAATCCCTCACAATAAA 479 CBL NM_005188 4885116 867 D-003003-08 CCAGAAAGCTTTGGTCATT 480 CBLB CBLB NM_170662 29366807 868 D-003004-05 GACCATACCTCATAACAAG 481 CBLB NM_170662 29366807 868 D-003004-06 TGAAAGACCTCCACCAATC 482 CBLB NM_170662 29366807 868 D-003004-07 GATGAAGGCTCCAGGTGTT 483 CBLB NM_170662 29366807 868 D-003004-08 TATCAGCATTTACGACTTA 484 EIF4EBP1 EIF4EBP1 NM_004095 20070179 1978 D-003005-05 GCAATAGCCCAGAAGATAA 485 EIF4EBP1 NM_004095 20070179 1978 D-003005-06 CGCAATAGCCCAGAAGATA 486 EIF4EBP1 NM_004095 20070179 1978 D-003005-07 GAGATGGACATTTAAAGCA 487 EIF4EBP1 NM_004095 20070179 1978 D-003005-08 CAATAGCCCAGAAGATAAG 488 FOXO1A FOXO1A NM_002015 9257221 2308 D-003006-05 CCAGGCATCTCATAACAAA 489 FOXO1A NM_002015 9257221 2308 D-003006-06 CCAGATGCCTATACAAACA 490 FOXO1A NM_002015 9257221 2308 D-003006-07 GGAGGTATGAGTCAGTATA 491 FOXO1A NM_002015 9257221 2308 D-003006-08 GAGGTATGAGTCAGTATAA 492 FOXO3A FOXO3A NM_001455 4503738 2309 D-003007-01 CAATAGCAACAAGTATACC 493 FOXO3A NM_001455 4503738 2309 D-003007-02 TGAAGTCCAGGACGATGAT 494 FOXO3A NM_001455 4503738 2309 D-003007-03 TGTCACACTATGGTAACCA 495 FOXO3A NM_001455 4503738 2309 D-003007-04 TGTTCAATGGGAGCTTGGA 496 FRAP1 FRAP1 NM_004958 19924298 2475 D-003008-05 GAGAAGAAATGGAAGAAAT 497 FRAP1 NM_004958 19924298 2475 D-003008-06 CCAAAGTGCTGCAGTACTA 498 FRAP1 NM_004958 19924298 2475 D-003008-07 GAGCATGCCGTCAATAATA 499 FRAP1 NM_004958 19924298 2475 D-003008-08 GGTCTGAACTGAATGAAGA 500 GSK3A GSK3A NM_019884 11995473 2931 D-003009-05 GGACAAAGGTGTTCAAATC 501 GSK3A NM_019884 11995473 2931 D-003009-06 GAACCCAGCTGCCTAACAA 502 GSK3A NM_019884 11995473 2931 D-003009-07 GCGCACAGCTTCTTTGATG 503 GSK3A NM_019884 11995473 2931 D-003009-08 GCTCTAGCCTGCTGGAGTA 504 GSK3B GSK3B NM_002093 21361339 2932 D-003010-05 GAAGAAAGATGAGGTCTAT 505 GSK3B NM_002093 21361339 2932 D-003010-06 GGACCCAAATGTCAAACTA 506 GSK3B NM_002093 21361339 2932 D-003010-07 GAAATGAACCCAAACTACA 507 GSK3B NM_002093 21361339 2932 D-003010-08 GATGAGGTCTATCTTAATC 508 IGF1 IGF1 NM_000618 D-003011-05 GGAAGTACATTTGAAGAAC 509 IGF1 NM_000618 D-003011-06 AGAAGGAAGTACATTTGAA 510 IGF1 NM_000618 D-003011-07 CCTCAAGCCTGCCAAGTCA 511 IGF1 NM_000618 D-003011-08 GGTGGATGCTCTTCAGTTC 512 IGF1R IGF1R NM_000875 11068002 3480 D-003012-05 CAACGAAGCTTCTGTGATG 513 IGF1R NM_000875 11068002 3480 D-003012-06 GGCCAGAAATGGAGAATAA 514 IGF1R NM_000875 11068002 3480 D-003012-07 GAAGCACCCTTTAAGAATG 515 IGF1R NM_000875 11068002 3480 D-003012-08 GCAGACACCTACAACATCA 516 INPP5D INPP5D NM_005541 5031798 3635 D-003013-05 GGAATTGCGTTTACACTTA 517 INPP5D NM_005541 5031798 3635 D-003013-06 GGAAACTGATCATTAAGAA 518 INPP5D NM_005541 5031798 3635 D-003013-07 CGACAGGGATGAAGTACAA 519 INPP5D NM_005541 5031798 3635 D-003013-08 AAACGCAGCTGCCCATCTA 520 INSR INSR NM_000208 4557883 3643 D-003014-05 GGAAGACGTTTGAGGATTA 521 INSR NM_000208 4557883 3643 D-003014-06 GAACAAGGCTCCCGAGAGT 522 INSR NM_000208 4557883 3643 D-003014-07 GGAGAGACCTTGGAAATTG 523 INSR NM_000208 4557883 3643 D-003014-08 GGACGGAACCCACCTATTT 524 IRS1 IRS1 NM_005544 5031804 3667 D-003015-05 AAAGAGGTCTGGCAAGTGA 525 IRS1 NM_005544 5031804 3667 D-003015-06 GAACCTGATTGGTATCTAC 526 IRS1 NM_005544 5031804 3667 D-003015-07 CCACGGCGATCTAGTGCTT 527 IRS1 NM_005544 5031804 3667 D-003015-08 GTCAGTCTGTCGTCCAGTA 528 MLLT7 MLLT7 NM_005938 5174578 4303 D-003016-05 GGACTGGACTTCAACTTTG 529 MLLT7 NM_005938 5174578 4303 D-003016-06 CCACGAAGCAGTTCAAATG 530 MLLT7 NM_005938 5174578 4303 D-003016-07 GAGAAGCGACTGACACTTG 531 MLLT7 NM_005938 5174578 4303 D-003016-08 GACCAGAGATCGCTAACCA 532 PDPK1 PDPK1 NM_002613 4505694 5170 D-003017-05 CAAGAGACCTCGTGGAGAA 533 PDPK1 NM_002613 4505694 5170 D-003017-06 GACCAGAGGCCAAGAATTT 534 PDPK1 NM_002613 4505694 5170 D-003017-07 GGAAACGAGTATCTTATAT 535 PDPK1 NM_002613 4505694 5170 D-003017-08 GAGAAGCGACATATCATAA 536 PIK3CA PIK3CA NM_006218 5453891 5290 D-003018-05 GCTATCATCTGAACAATTA 537 PIK3CA NM_006218 5453891 5290 D-003018-06 GGATAGAGGCCAAATAATA 538 PIK3CA NM_006218 5453891 5290 D-003018-07 GGACAACTGTTTCATATAG 539 PIK3CA NM_006218 5453891 5290 D-003018-08 GCCAGTACCTCATGGATTA 540 PIK3CB PIK3CB NM_006219 5453893 5291 D-003019-05 CGACAAGACTGCCGAGAGA 541 PIK3CB NM_006219 5453893 5291 D-003019-06 TCAAGTGTCTCCTAATATG 542 PIK3CB NM_006219 5453893 5291 D-003019-07 GGATTCAGTTGGAGTGATT 543 PIK3CB NM_006219 5453893 5291 D-003019-08 TTTCAAGTGTCTCCTAATA 544 PIK3R1 PIK3R1 NM_181504 32455251 5295 D-003020-05 GGAAATATGGCTTCTCTGA 545 PIK3R1 NM_181504 32455251 5295 D-003020-06 GAAAGACGAGAGACCAATA 546 PIK3R1 NM_181504 32455251 5295 D-003020-07 GTAAAGCATTGTGTCATAA 547 PIK3R1 NM_181504 32455251 5295 D-003020-08 GGATCAAGTTGTCAAAGAA 548 PIK3R2 PIK3R2 NM_005027 4826907 5296 D-003021-05 GGAAAGGCGGGAACAATAA 549 PIK3R2 NM_005027 4826907 5296 D-003021-06 GATGAAGCGTACTGCAATT 550 PIK3R2 NM_005027 4826907 5296 D-003021-07 GGACAGCGAATCTCACTAC 551 PIK3R2 NM_005027 4826907 5296 D-003021-08 GCAAGATCCGAGACCAGTA 552 PPP2R2B PPP2R2B NM_004576 4758953 5521 D-003022-05 GAATGCAGCTTACTTTCTT 553 PPP2R2B NM_004576 4758953 5521 D-003022-06 GACCGAAGCTGACATTATC 554 PPP2R2B NM_004576 4758953 5521 D-003022-07 TCGATTACCTGAAGAGTTT 555 PPP2R2B NM_004576 4758953 5521 D-003022-08 CCTGAAGAGTTTAGAAATA 556 PTEN PTEN NM_000314 4506248 5728 D-003023-05 GTGAAGATCTTGACCAATG 557 PTEN NM_000314 4506248 5728 D-003023-06 GATCAGCATACACAAATTA 558 PTEN NM_000314 4506248 5728 D-003023-07 GGCGCTATGTGTATTATTA 559 PTEN NM_000314 4506248 5728 D-003023-08 GTATAGAGCGTGCAGATAA 560 RPS6 RPS6 NM_001010 17158043 6194 D-003024-05 GCCAGAAACTCATTGAAGT 561 RPS6 NM_001010 17158043 6194 D-003024-06 GGATATTCCTGGACTGACT 562 RPS6 NM_001010 17158043 6194 D-003024-07 CCAAGGAGAACTGGAGAAA 563 RPS6 NM_001010 17158043 6194 D-003024-08 GCGTATGGCCACAGAAGTT 564 RPS6KA1 RPS6KA1 NM_002953 20149546 6195 D-003025-05 GATGACACCTTCTACTTTG 565 RPS6KA1 NM_002953 20149546 6195 D-003025-06 GAGAATGGGCTCCTCATGA 566 RPS6KA1 NM_002953 20149546 6195 D-003025-07 CAAGCGGGATCCTTCAGAA 567 RPS6KA1 NM_002953 20149546 6195 D-003025-08 CCACCGGCCTGATGGAAGA 568 RPS6KA3 RPS6KA3 NM_004586 4759049 6197 D-003026-05 GAAGGGAAGTTGTATCTTA 569 RPS6KA3 NM_004586 4759049 6197 D-003026-06 GAAAGTATGTGTATGTAGT 570 RPS6KA3 NM_004586 4759049 6197 D-003026-07 GGACAGCATCCAAACATTA 571 RPS6KA3 NM_004586 4759049 6197 D-003026-08 GGAGGTGAATTGCTGGATA 572 SGK SGK NM_005627 5032090 6446 D-003027-01 TTAATGGTGGAGAGTTGTT 573 SGK NM_005627 5032090 6446 D-003027-04 ATTAACTGGGATGATCTCA 574 SGK NM_005627 25168262 6446 D-003027-05 GAAGAAAGCAATCCTGAAA 575 SGK NM_005627 25168262 6446 D-003027-06 AAACACAGCTGAAATGTAC 576 TSC1 TSC1 NM_000368 24475626 7248 D-003028-05 GAAGATGGCTATTCTGTGT 577 TSC1 NM_000368 24475626 7248 D-003028-06 TATGAAGGCTCGAGAGTTA 578 TSC1 NM_000368 24475626 7248 D-003028-07 CGACACGGCTGATAACTGA 579 TSC1 NM_000368 24475626 7248 D-003028-08 CGGCTGATGTTGTTAAATA 580 TSC2 TSC2 NM_000548 10938006 7249 D-003029-05 GCATTAATCTCTTACCATA 581 TSC2 NM_000548 10938006 7249 D-003029-06 CCAATGTCCTCTTGTCTTT 582 TSC2 NM_000548 10938006 7249 D-003029-07 GGAGACACATCACCTACTT 583 TSC2 NM_000548 10938006 7249 D-003029-08 TCACCAGGCTCATCAAGAA 584 XPO1 XPO1 NM_003400 8051634 7514 D-003030-05 GAAAGTCTCTGTCAAAATA 585 XPO1 NM_003400 8051634 7514 D-003030-06 GCAATAGGCTCCATTAGTG 586 XPO1 NM_003400 8051634 7514 D-003030-07 GGAACATGATCAACTTATA 587 XPO1 NM_003400 8051634 7514 D-003030-08 GGATACAGATTCCATAAAT 588

TABLE VII Gene SEQ. Name Acc # GI L.L. Duplex # Sequence ID NO. ABL1 ABL1 NM_007313 6382057 25 D-003100-05 GGAAATCAGTGACATAGTG 589 ABL1 NM_007313 6382057 25 D-003100-06 GGTCCACACTGCAATGTTT 590 ABL1 NM_007313 6382057 25 D-003100-07 GAAGGAAATCAGTGACATA 591 ABL1 NM_007313 6382057 25 D-003100-08 TCACTGAGTTCATGACCTA 592 ABL2 ABL2 NM_007314 6382061 27 D-003101-05 GAAATGGAGCGAACAGATA 593 ABL2 NM_007314 6382061 27 D-003101-06 GAGCCAAATTTCCTATTAA 594 ABL2 NM_007314 6382061 27 D-003101-07 GTAATAAGCCTACAGTCTA 595 ABL2 NM_007314 6382061 27 D-003101-08 GGAGTGAAGTTCGCTCTAA 596 ACK1 ACK1 NM_005781 8922074 10188 D-003102-05 AAACGCAAGTCGTGGATGA 597 ACK1 NM_005781 8922074 10188 D-003102-06 GCAAGTCGTGGATGAGTAA 598 ACK1 NM_005781 8922074 10188 D-003102-07 GAGCACTACCTCAGAATGA 599 ACK1 NM_005781 8922074 10188 D-003102-08 TCAGCAGCACCCACTATTA 600 ALK ALK NM_004304 29029631 238 D-003103-05 GACAAGATCCTGCAGAATA 601 ALK NM_004304 29029631 238 D-003103-06 GGAAGAGTCTGGCAGTTGA 602 ALK NM_004304 29029631 238 D-003103-07 GCACGTGGCTCGGGACATT 603 ALK NM_004304 29029631 238 D-003103-08 GAACTGCAGTGAAGGAACA 604 AXL AXL NM_021913 21536465 558 D-003104-05 GGTCAGAGCTGGAGGATTT 605 AXL NM_021913 21536465 558 D-003104-06 GAAAGAAGGAGACCCGTTA 606 AXL NM_021913 21536465 558 D-003104-07 CCAAGAAGATCTACAATGG 607 AXL NM_021913 21536465 558 D-003104-08 GGAACTGCATGCTGAATGA 608 BLK BLK NM_001715 4502412 640 D-003105-05 GAGGATGCCTGCTGGATTT 609 BLK NM_001715 4502412 640 D-003105-06 ACATGAAGGTGGCCATTAA 610 BLK NM_001715 4502412 640 D-003105-07 GGTCAGCGCCCAAGACAAG 611 BLK NM_001715 4502412 640 D-003105-08 GAAACTCGGGTCTGGACAA 612 BMX BMX NM_001721 21359831 660 D-003106-05 AAACAAACCTTTCCTACTA 613 BMX NM_001721 21359831 660 D-003106-06 GAAGGAGCATTTATGGTTA 614 BMX NM_001721 21359831 660 D-003106-07 GAGAAGAGATTACCTTGTT 615 BMX NM_001721 21359831 660 D-003106-08 GTAAGGCTGTGAATGATAA 616 BTK BTK NM_000061 4557376 695 D-003107-05 GAACAGGAATGGAAGCTTA 617 BTK NM_000061 4557376 695 D-003107-06 GCTATGGGCTGCCAAATTT 618 BTK NM_000061 4557376 695 D-003107-07 GAAAGCAACTTACCATGGT 619 BTK NM_000061 4557376 695 D-003107-08 GGTAAACGATCAAGGAGTT 620 C20orf64 C20orf64 NM_033550 19923655 11285 D-003108-05 CAACTTAGCCAAGACAATT 621 C20orf64 NM_033550 19923655 11285 D-003108-06 GAAATTGAAGGCTCAGTGA 622 C20orf64 NM_033550 19923655 11285 D-003108-07 TGGAACAGCTGAACATTGT 623 C20orf64 NM_033550 19923655 11285 D-003108-08 GCTTCCAACTGCTTATATA 624 CSF1R CSF1R NM_005211 27262658 1436 D-003109-05 GGAGAGCTCTGACGTTTGA 625 CSF1R NM_005211 27262658 1436 D-003109-06 CAACAACGCTACCTTCCAA 626 CSF1R NM_005211 27262658 1436 D-003109-07 CCACGCAGCTGCCTTACAA 627 CSF1R NM_005211 27262658 1436 D-003109-08 GGAACAACCTGCAGTTTGG 628 CSK CSK NM_004383 4758077 1445 D-003110-05 CAGAATGTATTGCCAAGTA 629 CSK NM_004383 4758077 1445 D-003110-06 GAACAAAGTCGCCGTCAAG 630 CSK NM_004383 4758077 1445 D-003110-07 GCGAGTGCCTTATCCAAGA 631 CSK NM_004383 4758077 1445 D-003110-08 GGAGAAGGGCTACAAGATG 632 DDR1 DDR1 NM_013994 7669484 780 D-003111-05 GGAGATGGAGTTTGAGTTT 633 DDR1 NM_013994 7669484 780 D-003111-06 CAGAGGCCCTGTCATCTTT 634 DDR1 NM_013994 7669484 780 D-003111-07 GCTGGTAGCTGTCAAGATC 635 DDR1 NM_013994 7669484 780 D-003111-08 TGAAAGAGGTGAAGATCAT 636 DDR2 DDR2 NM_006182 5453813 4921 D-003112-05 GGTAAGAACTACACAATCA 637 DDR2 NM_006182 5453813 4921 D-003112-06 GAACGAGAGTGCCACCAAT 638 DDR2 NM_006182 5453813 4921 D-003112-07 ACACCAATCTGAAGTTTAT 639 DDR2 NM_006182 5453813 4921 D-003112-08 CAACAAGAATGCCAGGAAT 640 DKFZp761 P1010 DKFZp761 NM_018423 8922178 55359 D-003113-05 CCTAGAAGCTGCCATTAAA 641 P1010 DKFZp761 NM_018423 8922178 55359 D-003113-06 GATTAGGCCTGGCTTATGA 642 P1010 DKFZp761 NM_018423 8922178 55359 D-003113-07 CCCAGTAGCTGCACACATA 643 P1010 DKFZp761 NM_018423 8922178 55359 D-003113-08 GGTGGTACCTGAACTGTAT 644 P1010 EGFR EGFR NM_005228 4885198 1956 D-003114-05 GAAGGAAACTGAATTCAAA 645 EGFR NM_005228 4885198 1956 D-003114-06 GGAAATATGTACTACGAAA 646 EGFR NM_005228 4885198 1956 D-003114-07 CCACAAAGCAGTGAATTTA 647 EGFR NM_005228 4885198 1956 D-003114-08 GTAACAAGCTCACGCAGTT 648 EPHA1 EPHA1 NM_005232 4885208 2041 D-003115-05 GACCAGAGCTTCACCATTC 649 EPHA1 NM_005232 4885208 2041 D-003115-06 GCAAGACTGTGGCCATTAA 650 EPHA1 NM_005232 4885208 2041 D-003115-07 GGGCGAACCTGACCTATGA 651 EPHA1 NM_005232 4885208 2041 D-003115-08 GATTGTAGCCGTCATCTTT 652 EPHA2 EPHA2 NM_004431 4758277 1969 D-003116-05 GGAGGGATCTGGCAACTTG 653 EPHA2 NM_004431 4758277 1969 D-003116-06 GCAGCAAGGTGCACGAATT 654 EPHA2 NM_004431 4758277 1969 D-003116-07 GGAGAAGGATGGCGAGTTC 655 EPHA2 NM_004431 4758277 1969 D-003116-08 GAAGTTCACTACCGAGATC 656 EPHA3 EPHA3 NM_005233 21361240 2042 D-003117-05 GATCGGACCTCCAGAAATA 657 EPHA3 NM_005233 21361240 2042 D-003117-06 GAACTCAGCTCAGAAGATT 658 EPHA3 NM_005233 21361240 2042 D-003117-07 GCAAGAGGCACAAATGTTA 659 EPHA3 NM_005233 21361240 2042 D-003117-08 GAGCATCAGTTTACAAAGA 660 EPHA4 EPHA4 NM_004438 4758279 2043 D-003118-05 GGTCTGGGATGAAGTATTT 661 EPHA4 NM_004438 4758279 2043 D-003118-06 GAATGAAGTTACCTTATTG 662 EPHA4 NM_004438 4758279 2043 D-003118-07 GAACTTGGGTGGATAGCAA 663 EPHA4 NM_004438 4758279 2043 D-003118-08 GAGATTAAATTCACCTTGA 664 EPHA7 EPHA7 NM_004440 4758281 2045 D-003119-05 GAAAAGAGATGTTGCAGTA 665 EPHA7 NM_004440 4758281 2045 D-003119-06 CTAGATGCCTCCTGTATTA 666 EPHA7 NM_004440 4758281 2045 D-003119-07 AGAAGAAGGTTATCGTTTA 667 EPHA7 NM_004440 4758281 2045 D-003119-08 TAGCAAAGCTGACCAAGAA 668 EPHA8 EPHA8 NM_020526 18201903 2046 D-003120-05 GAAGATGCACTATCAGAAT 669 EPHA8 NM_020526 18201903 2046 D-003120-06 GAGAAGATGCACTATCAGA 670 EPHA8 NM_020526 18201903 2046 D-003120-07 AACCTGATCTCCAGTGTGA 671 EPHA8 NM_020526 18201903 2046 D-003120-08 TCTCAGACCTGGGCTATGT 672 EPHB1 EPHB1 NM_004441 21396502 2047 D-003121-05 GCGATAAGCTCCAGCATTA 673 EPHB1 NM_004441 21396502 2047 D-003121-06 GAAACGGGCTTATAGCAAA 674 EPHB1 NM_004441 21396502 2047 D-003121-07 GGATGAAGATCTACATTGA 675 EPHB1 NM_004441 21396502 2047 D-003121-08 GCACGTCTCTGTCAACATC 676 EPHB2 EPHB2 NM_017449 17975764 2048 D-003122-05 ACTATGAGCTGCAGTACTA 677 EPHB2 NM_017449 17975764 2048 D-003122-06 GTACAACGCCACAGCCATA 678 EPHB2 NM_017449 17975764 2048 D-003122-07 GGAAAGCAATGACTGTTCT 679 EPHB2 NM_017449 17975764 2048 D-003122-08 CGGACAAGCTGCAACACTA 680 EPHB3 EPHB3 NM_004443 17975767 2049 D-003123-05 GGTGTGATCTCCAATGTGA 681 EPHB3 NM_004443 17975767 2049 D-003123-06 GGGATGACCTCCTGTACAA 682 EPHB3 NM_004443 17975767 2049 D-003123-07 CAGAAGACCTGCTCCGTAT 683 EPHB3 NM_004443 17975767 2049 D-003123-08 GAGATGAAGTACTTTGAGA 684 EPHB4 EPHB4 NM_004444 17975769 2050 D-003124-05 GGACAAACACGGACAGTAT 685 EPHB4 NM_004444 17975769 2050 D-003124-06 GTACTAAGGTCTACATCGA 686 EPHB4 NM_004444 17975769 2050 D-003124-07 GGAGAGAAGCAGAATATTC 687 EPHB4 NM_004444 17975769 2050 D-003124-08 GCCAATAGCCACTCTAACA 688 EPHB6 EPHB6 NM_004445 4758291 2051 D-003125-05 GGAAGTCGATCCTGCTTAT 689 EPHB6 NM_004445 4758291 2051 D-003125-06 GGACCAAGGTGGACACAAT 690 EPHB6 NM_004445 4758291 2051 D-003125-07 TGTGGGAAGTGATGAGTTA 691 EPHB6 NM_004445 4758291 2051 D-003125-08 CGGGAGACCTTCACCCTTT 692 ERBB2 ERBB2 NM_004448 4758297 2064 D-003126-05 GGACGAATTCTGCACAATG 693 ERBB2 NM_004448 4758297 2064 D-003126-06 GACGAATTCTGCACAATGG 694 ERBB2 NM_004448 4758297 2064 D-003126-07 CTACAACACAGACACGTTT 695 ERBB2 NM_004448 4758297 2064 D-003126-08 AGACGAAGCATACGTGATG 696 ERBB3 ERBB3 NM_001982 4503596 2065 D-003127-05 AAGAGGATGTCAACGGTTA 697 ERBB3 NM_001982 4503596 2065 D-003127-06 GAAGACTGCCAGACATTGA 698 ERBB3 NM_001982 4503596 2065 D-003127-07 GACAAACACTGGTGCTGAT 699 ERBB3 NM_001982 4503596 2065 D-003127-08 GCAGTGGATTCGAGAAGTG 700 ERBB4 ERBB4 NM_005235 4885214 2066 D-003128-05 GAGGAAAGATGCCAATTAA 701 ERBB4 NM_005235 4885214 2066 D-003128-06 GCAGGAAACATCTATATTA 702 ERBB4 NM_005235 4885214 2066 D-003128-07 GATCACAACTGCTGCTTAA 703 ERBB4 NM_005235 4885214 2066 D-003128-08 CCTCAAAGATACCTAGTTA 704 FER FER NM_005246 4885230 2241 D-003129-05 GGAGTGACCTGAAGAATTC 705 FER NM_005246 4885230 2241 D-003129-06 TAAAGCAGATTCCCATTAA 706 FER NM_005246 4885230 2241 D-003129-07 GGAAAGTACTGTCCAAATG 707 FER NM_005246 4885230 2241 D-003129-08 GAACAACGGCTGCTAAAGA 708 FES FES NM_002005 13376997 2242 D-003130-05 CGAGGATCCTGAAGCAGTA 709 FES NM_002005 13376997 2242 D-003130-06 AGGAATACCTGGAGATTAG 710 FES NM_002005 13376997 2242 D-003130-07 CAACAGGAGCTCCGGAATG 711 FES NM_002005 13376997 2242 D-003130-08 GGTGTTGGGTGAGCAGATT 712 FGFR1 FGFR1 NM_000604 13186232 2260 D-003131-05 TAAGAAATGTCTCCTTTGA 713 FGFR1 NM_000604 13186232 2260 D-003131-06 GAAGACTGCTGGAGTTAAT 714 FGFR1 NM_000604 13186232 2260 D-003131-07 GATGGTCCCTTGTATGTCA 715 FGFR1 NM_000604 13186232 2260 D-003131-08 CTTAAGAAATGTCTCCTTT 716 FGFR2 FGFR2 NM_000141 13186239 2263 D-003132-05 CCAAATCTCTCAACCAGAA 717 FGFR2 NM_000141 13186239 2263 D-003132-06 GAACAGTATTCACCTAGTT 718 FGFR2 NM_000141 13186239 2263 D-003132-07 GGCCAACACTGTCAAGTTT 719 FGFR2 NM_000141 13186239 2263 D-003132-08 GTGAAGATGTTGAAAGATG 720 FGFR3 FGFR3 NM_000142 13112046 2261 D-003133-05 TGTCGGACCTGGTGTCTGA 721 FGFR3 NM_000142 13112046 2261 D-003133-06 GCATCAAGCTGCGGCATCA 722 FGFR3 NM_000142 13112046 2261 D-003133-07 GGACGGCACACCCTACGTT 723 FGFR3 NM_000142 13112046 2261 D-003133-08 TGCACAACCTCGACTACTA 724 FGFR4 FGFR4 NM_002011 13112051 2264 D-003134-05 GCACTGGAGTCTCGTGATG 725 FGFR4 NM_002011 13112051 2264 D-003134-06 CATAGGGACCTCTCGAATA 726 FGFR4 NM_002011 13112051 2264 D-003134-07 ATACGGACATCATCCTGTA 727 FGFR4 NM_002011 13112051 2264 D-003134-08 ATAGGGACCTCTCGAATAG 728 FGR FGR NM_005248 4885234 2268 D-003135-05 GCGATCATGTGAAGCATTA 729 FGR NM_005248 4885234 2268 D-003135-06 TCACTGAGCTCATCACCAA 730 FGR NM_005248 4885234 2268 D-003135-07 GAAGAGTGGTACTTTGGAA 731 FGR NM_005248 4885234 2268 D-003135-08 CCCAGAAGCTGCCCTCTTT 732 FLT1 FLT1 NM_002019 4503748 2321 D-003136-05 GAGCAAACGTGACTTATTT 733 FLT1 NM_002019 4503748 2321 D-003136-06 CCAAATGGGTTTCATGTTA 734 FLT1 NM_002019 4503748 2321 D-003136-07 CAACAAGGATGCAGCACTA 735 FLT1 NM_002019 4503748 2321 D-003136-08 GGACGTAACTGAAGAGGAT 736 FLT3 FLT3 NM_004119 4758395 2322 D-003137-05 GAAGGCATCTACACCATTA 737 FLT3 NM_004119 4758395 2322 D-003137-06 GAAGGAGTCTGGAATAGAA 738 FLT3 NM_004119 4758395 2322 D-003137-07 GAATTTAAGTCGTGTGTTC 739 FLT3 NM_004119 4758395 2322 D-003137-08 GGAATTCATTTCACTCTGA 740 FLT4 FLT4 NM_002020 4503752 2324 D-003138-05 GCAAGAACGTGCATCTGTT 741 FLT4 NM_002020 4503752 2324 D-003138-06 GCGAATACCTGTCCTACGA 742 FLT4 NM_002020 4503752 2324 D-003138-07 GAAGACATTTGAGGAATTC 743 FLT4 NM_002020 4503752 2324 D-003138-08 GAGCAGCCATTCATCAACA 744 FRK FRK NM_002031 4503786 2444 D-003139-05 GAAACAGACTCTTCATATT 745 FRK NM_002031 4503786 2444 D-003139-06 GAACAATACCACTCCAGTA 746 FRK NM_002031 4503786 2444 D-003139-07 CAAGACCGGTTCCTTTCTA 747 FRK NM_002031 4503786 2444 D-003139-08 GCAAGAATATCTCCAAAAT 748 FYN FYN NM_002037 23510344 2534 D-003140-05 GGAATGGACTCATATGCAA 749 FYN NM_002037 23510344 2534 D-003140-06 GCAGAAGAGTGGTACTTTG 750 FYN NM_002037 23510344 2534 D-003140-07 CAAAGGAAG1TTACTGGAT 751 FYN NM_002037 23510344 2534 D-003140-08 GAAGAGTGGTACTTTGGAA 752 HCK HCK NM_002110 4504356 3055 D-003141-05 GAGATACCGTGAAACATTA 753 HCK NM_002110 4504356 3055 D-003141-06 GCAGGGAGATACCGTGAAA 754 HCK NM_002110 4504356 3055 D-003141-07 CATCGTGGTTGCCCTGTAT 755 HCK NM_002110 4504356 3055 D-003141-08 TGTGTAAGATTGCTGACTT 756 ITK ITK NM_005546 21614549 3702 D-003144-05 CAAATAATCTGGAAACCTA 757 ITK NM_005546 21614549 3702 D-003144-06 GAAGAAACGAGGAATAATA 758 ITK NM_005546 21614549 3702 D-003144-07 GAAACTCTCTCATCCCAAA 759 ITK NM_005546 21614549 3702 D-003144-08 GGAATGGGCATGAAGGATA 760 JAK1 JAK1 NM_002227 4504802 3716 D-003145-05 CCACATAGCTGATCTGAAA 761 JAK1 NM_002227 4504802 3716 D-003145-06 TGAAATCACTCACATTGTA 762 JAK1 NM_002227 4504802 3716 D-003145-07 TAAGGAACCTCTATCATGA 763 JAK1 NM_002227 4504802 3716 D-003145-08 GCAGGTGGCTGTTAAATCT 764 JAK2 JAK2 NM_004972 13325062 3717 D-003146-05 GCAAATAGATCCAGTTCTT 765 JAK2 NM_004972 13325062 3717 D-003146-06 GAGCAAAGATCCAAGACTA 766 JAK2 NM_004972 13325062 3717 D-003146-07 GCCAGAAACTTGAAACTTA 767 JAK2 NM_004972 13325062 3717 D-003146-08 GTACAGATTTCGCAGATTT 768 JAK3 JAK3 NM_000215 4557680 3718 D-003147-05 GCGCCTATCTTTCTCCTTT 769 JAK3 NM_000215 4557680 3718 D-003147-06 CCAGAAATCGTAGACATTA 770 JAK3 NM_000215 4557680 3718 D-003147-07 CCTCATCTCTTCAGACTAT 771 JAK3 NM_000215 4557680 3718 D-003147-08 TGTACGAGCTCTTCACCTA 772 KDR KDR NM_002253 11321596 3791 D-003148-05 GGAAATCTCTTGCAAGCTA 773 KDR NM_002253 11321596 3791 D-003148-06 GATTACAGATCTCCATTTA 774 KDR NM_002253 11321596 3791 D-003148-07 GCAGACAGATCTACGTTTG 775 KDR NM_002253 11321596 3791 D-003148-08 GCGATGGCCTCTTCTGTAA 776 KIAA1079 KIAA1079 NM_014916 7662475 22853 D-003149-05 GAAATTCTCTCAACTGATG 777 KIAA1079 NM_014916 7662475 22853 D-003149-06 GCAGAGGTCTTCACACTTT 778 KIAA1079 NM_014916 7662475 22853 D-003149-07 TAAATGATCTTCAGACAGA 779 KIAA1079 NM_014916 7662475 22853 D-003149-08 GAGCAGCCCTACTCTGATA 780 KIT KIT NM_000222 4557694 3815 D-003150-05 AAACACGGCTTAAGCAATT 781 KIT NM_000222 4557694 3815 D-003150-06 GAACAGAACCTTCACTGAT 782 KIT NM_000222 4557694 3815 D-003150-07 GGGAAGCCCTCATGTCTGA 783 KIT NM_000222 4557694 3815 D-003150-08 GCAATTCCATTTATGTGTT 784 LCK LCK NM_005356 20428651 3932 D-003151-05 GAACTGCCATTATCCCATA 785 LCK NM_005356 20428651 3932 D-003151-06 GAGAGGTGGTGAAACATTA 786 LCK NM_005356 20428651 3932 D-003151-07 GGGCCAAGTTTCCCATTAA 787 LCK NM_005356 20428651 3932 D-003151-08 GCACGCTGCTCATCCGAAA 788 LTK LTK NM_002344 4505044 4058 D-003152-05 TGAATTCACTCCTGCCAAT 789 LTK NM_002344 4505044 4058 D-003152-06 GTGGCAACCTCAACACTGA 790 LTK NM_002344 4505044 4058 D-003152-07 GGAGCTAGCTGTGGATAAC 791 LTK NM_002344 4505044 4058 D-003152-08 GCAAGTTTCGCCATCAGAA 792 LYN LYN NM_002350 4505054 4067 D-003153-05 GCAGATGGCTTGTGCAGAA 793 LYN NM_002350 4505054 4067 D-003153-06 GGAGAAGGCTTGTATTAGT 794 LYN NM_002350 4505054 4067 D-003153-07 GATGAGCTCTATGACATTA 795 LYN NM_002350 4505054 4067 D-003153-08 GGTGCTAAGTTCCCTATTA 796 MATK MATK NM_002378 21450841 4145 D-003154-05 TGAAGAATATCAAGTGTGA 797 MATK NM_002378 21450841 4145 D-003154-06 CCGCTCAGCTCCTGCAGTT 798 MATK NM_002378 21450841 4145 D-003154-07 TACTGAACCTGCAGCATTT 799 MATK NM_002378 21450841 4145 D-003154-08 TGGGAGGTCTTCTCATATG 800 MERTK MERTK NM_006343 5453737 10461 D-003155-05 GAACTTACCTTACATAGCT 801 MERTK NM_006343 5453737 10461 D-003155-06 GGACCTGCATACTTACTTA 802 MERTK NM_006343 5453737 10461 D-003155-07 TGACAGGAATCTTCTAATT 803 MERTK NM_006343 5453737 10461 D-003155-08 GGTAATGGCTCAGTCATGA 804 MET MET NM_000245 4557746 4233 D-003156-05 GAAAGAACCTCTCAACATT 805 MET NM_000245 4557746 4233 D-003156-06 GGACAAGGCTGACCATATG 806 MET NM_000245 4557746 4233 D-003156-07 CCAATGACCTGCTGAAATT 807 MET NM_000245 4557746 4233 D-003156-08 GAGCATACATTAAACCAAA 808 MST1R MST1R NM_002447 4505264 4486 D-003157-05 GGATGGAGCTGCTGGCTTT 809 MST1R NM_002447 4505264 4486 D-003157-06 CTGCAGACCTATAGATTTA 810 MST1R NM_002447 4505264 4486 D-003157-07 GCACCTGTCTCACTCTTGA 811 MST1R NM_002447 4505264 4486 D-003157-08 GAAAGAGTCCATCCAGCTA 812 MUSK MUSK NM_005592 5031926 4593 D-003158-05 GAAGAAGCCTCGGCAGATA 813 MUSK NM_005592 5031926 4593 D-003158-06 GTAATAATCTCCATCATGT 814 MUSK NM_005592 5031926 4593 D-003158-07 GGAATGAACTGAAAGTAGT 815 MUSK NM_005592 5031926 4593 D-003158-08 GAGATTTCCTGGACTAGAA 816 NTRK1 NTRK1 NM_002529 4585711 4914 D-003159-05 GGACAACCCTTTCGAGTTC 817 NTRK1 NM_002529 4585711 4914 D-003159-06 CCAGTGACCTCAACAGGAA 818 NTRK1 NM_002529 4585711 4914 D-003159-07 CCACAATACTTCAGTGATG 819 NTRK1 NM_002529 4585711 4914 D-003159-08 GAAGAGTGGTCTCCGTTTC 820 NTRK2 NTRK2 NM_006180 21361305 4915 D-00316D-05 GAACAGAAGTAATGAAATC 821 NTRK2 NM_006180 21361305 4915 D-00316D-06 GTAATGCTGTTTCTGCTTA 822 NTRK2 NM_006180 21361305 4915 D-00316D-07 GCAAGACACTCCAAGTTTG 823 NTRK2 NM_006180 21361305 4915 D-00316D-08 GAAAGTCTATCACATTATC 824 NTRK3 NTRK3 NM_002530 4505474 4916 D-003161-05 GAGCGAATCTGCTAGTGAA 825 NTRK3 NM_002530 4505474 4916 D-003161-06 GAAGTTCACTACAGAGAGT 826 NTRK3 NM_002530 4505474 4916 D-003161-07 GGTCGACGGTCCAAATTTG 827 NTRK3 NM_002530 4505474 4916 D-003161-08 GAATATCACTTCCATACAC 828 PDGFRA PDGFRA NM_006206 15451787 5156 D-003162-05 GAAACTTCCTGGACTATTT 829 PDGFRA NM_006206 15451787 5156 D-003162-06 GAGATTTGGTCAACTATTT 830 PDGFRA NM_006206 15451787 5156 D-003162-07 GCACGCCGCTTCCTGATAT 831 PDGFRA NM_006206 15451787 5156 D-003162-08 CATCAGAGCTGGATCTAGA 832 PDGFRB PDGFRB NM_002609 15451788 5159 D-003163-05 GAAAGGAGACGTCAAATAT 833 PDGFRB NM_002609 15451788 5159 D-003163-06 GGAATGAGGTGGTCAACTT 834 PDGFRB NM_002609 15451788 5159 D-003163-07 CAACGAGTCTCCAGTGCTA 835 PDGFRB NM_002609 15451788 5159 D-003163-08 GAGAGGACCTGCCGAGCAA 836 PTK2 PTK2 NM_005607 27886592 5747 D-003164-05 GAAGTTGGGTTGTCTAGAA 837 PTK2 NM_005607 27886592 5747 D-003164-06 GAAGAACAATGATGTAATC 838 PTK2 NM_005607 27886592 5747 D-003164-07 GGAAATTGCTTTGAAGTTG 839 PTK2 NM_005607 27886592 5747 D-003164-08 GGTTCAAGCTGGATTATTT 840 PTK2B PTK2B NM_004103 27886583 2185 D-003165-05 GAACATGGCTGACCTCATA 841 PTK2B NM_004103 27886583 2185 D-003165-06 GGACCACGCTGCTCTATTT 842 PTK2B NM_004103 27886583 2185 D-003165-07 GGACGAGGACTATTACAAA 843 PTK2B NM_004103 27886583 2185 D-003165-08 TGGCAGAGCTCATCAACAA 844 PTK6 PTK6 NM_005975 27886594 5753 D-003166-05 GAGAAAGTCCTGCCCGTTT 845 PTK6 NM_005975 27886594 5753 D-003166-06 TGAAGAAGCTGCGGCACAA 846 PTK6 NM_005975 27886594 5753 D-003166-07 CCGCGACTCTGATGAGAAA 847 PTK6 NM_005975 27886594 5753 D-003166-08 TGCCCGAGCTTGTGAACTA 848 PTK7 PTK7 NM_002821 27886610 5754 D-003167-05 GAGAGAAGCCCACTATTAA 849 PTK7 NM_002821 27886610 5754 D-003167-06 CGAGAGAAGCCCACTATTA 850 PTK7 NM_002821 27886610 5754 D-003167-07 GGAGGGAGTTGGAGATGTT 851 PTK7 NM_002821 27886610 5754 D-003167-08 GAAGACATGCCGCTATTTG 852 PTK9 PTK9 NM_002822 4506274 5756 D-003168-05 GAAGAACTACGACAGATTA 853 PTK9 NM_002822 4506274 5756 D-003168-09 GAAGGAGACTATTTAGAGT 854 PTK9 NM_002822 4506274 5756 D-003168-10 GAGCGGATGCTGTATTCTA 855 PTK9 NM_002822 4506274 5756 D-003168-11 CTGCAGACTTCCTTTATGA 856 PTK9L PTK9L NM_007284 31543446 11344 D-003169-05 AGAGAGAGCTCCAGCAGAT 857 PTK9L NM_007284 31543446 11344 D-003169-06 TTAACGAGGTGAAGACAGA 858 PTK9L NM_007284 31543446 11344 D-003169-07 ACACAGAGCCCACGGATGT 859 PTK9L NM_007284 31543446 11344 D-003169-08 GCTGGGATCAGGACTATGA 860 RET RET NM_000323 21536316 5979 D-003170-05 GCAAAGACCTGGAGAAGAT 861 RET NM_000323 21536316 5979 D-003170-06 GCACACGGCTGCATGAGAA 862 RET NM_000323 21536316 5979 D-003170-07 GAACTGGCCTGGAGAGAGT 863 RET NM_000323 21536316 5979 D-003170-08 TTAAATGGATGGCAATTGA 864 ROR1 ROR1 NM_005012 4826867 4919 D-003171-05 GCAAGCATCTTTACTAGGA 865 ROR1 NM_005012 4826867 4919 D-003171-06 GAGCAAGGCTAAAGAGCTA 866 ROR1 NM_005012 4826867 4919 D-003171-07 GAGAGCAACTTCATGTAAA 867 ROR1 NM_005012 4826867 4919 D-003171-08 GAGAATGTCCTGTGTCAAA 868 ROR2 ROR2 NM_004560 19743897 4920 D-003172-05 GGAACTCGCTGCTGCCTAT 869 ROR2 NM_004560 19743897 4920 D-003172-06 GCAGGTGCCTCCTCAGATG 870 ROR2 NM_004560 19743897 4920 D-003172-07 GCAATGTGCTAGTGTACGA 871 ROR2 NM_004560 19743897 4920 D-003172-08 GAAGACAGAATATGGTTCA 872 ROS1 ROS1 NM_002944 19924164 6098 D-003173-05 GAGGAGACCTTCTTACTTA 873 ROS1 NM_002944 19924164 6098 D-003173-06 TTACAGAGGTTCAGGATTA 874 ROS1 NM_002944 19924164 6098 D-003173-07 GAACAAACCTAAGCATGAA 875 ROS1 NM_002944 19924164 6098 D-003173-08 GAAAGAGCACTTCAAATAA 876 RYK RYK NM_002958 11863158 6259 D-003174-05 GAAAGATGGTTACCGAATA 877 RYK NM_002958 11863158 6259 D-003174-06 CAAAGTAGATTCTGAAGTT 878 RYK NM_002958 11863158 6259 D-003174-07 TCACTACGCTCTATCCTTT 879 RYK NM_002958 11863158 6259 D-003174-08 GGTGAAGGATATAGCAATA 880 SRC SRC NM_005417 21361210 6714 D-003175-05 GAGAACCTGGTGTGCAAAG 881 SRC NM_005417 21361210 6714 D-003175-09 GAGAGAACCTGGTGTGCAA 882 SRC NM_005417 21361210 6714 D-003175-10 GGAGTTTGCTGGACTTTCT 883 SRC NM_005417 21361210 6714 D-003175-11 GAAAGTGAGACCACGAAAG 884 SYK SYK NM_003177 21361552 6850 D-003176-05 GGAATAATCTCAAGAATCA 885 SYK NM_003177 21361552 6850 D-003176-06 GAACTGGGCTCTGGTAATT 886 SYK NM_003177 21361552 6850 D-003176-07 GGAAGAATCTGAGCAAATT 887 SYK NM_003177 21361552 6850 D-003176-08 GAACAGACATGTCAAGGAT 888 TEC TEC NM_003215 4507428 7006 D-003177-05 GAAATTGTCTAGTAAGTGA 889 TEC NM_003215 4507428 7006 D-003177-06 CACCTGAAGTGTTTAATTA 890 TEC NM_003215 4507428 7006 D-003177-07 GTACAAAGTCGCAATCAAA 891 TEC NM_003215 4507428 7006 D-003177-08 TGGAGGAGATTCTTATTAA 892 TEK TEK NM_000459 4557868 7010 D-003178-05 GAAAGAATATGCCTCCAAA 893 TEK NM_000459 4557868 7010 D-003178-06 GGAATGACATCAAATTTCA 894 TEK NM_000459 4557868 7010 D-003178-07 TGAAGTACCTGATATTCTA 895 TEK NM_000459 4557868 7010 D-003178-08 CGAAAGACCTACGTGAATA 896 TIE TIE NM_005424 4885630 7075 D-003179-05 GAGAGGAGGTTTATGTGAA 897 TIE NM_005424 4885630 7075 D-003179-06 GGGACAGCCTCTACCCTTA 898 TIE NM_005424 4885630 7075 D-003179-07 GAAGTTCTGTGCAAATTGG 899 TIE NM_005424 4885630 7075 D-003179-08 CAACATGGCCTCAGAACTG 900 TNK1 TNK1 NM_003985 4507610 8711 D-003180-05 GTTCTGGGCCTAAGTCTAA 901 TNK1 NM_003985 4507610 8711 D-003180-06 GAACTGGGTCTACAAGATC 902 TNK1 NM_003985 4507610 8711 D-003180-07 CGAGAGGTATCGGTCATGA 903 TNK1 NM_003985 4507610 8711 D-003180-08 GGCGCATCCTGGAGCATTA 904 TXK TXK NM_003328 4507742 7294 D-003181-05 GAACATCTATTGAGACAAG 905 TXK NM_003328 4507742 7294 D-003181-06 TCAAGGCACTTTATGATTT 906 TXK NM_003328 4507742 7294 D-003181-07 GGAGAGGAATGGCTATATT 907 TXK NM_003328 4507742 7294 D-003181-08 GGATATATGTGAAGGAATG 908 TYK2 TYK2 NM_003331 4507748 7297 D-003182-05 GAGGAGATCCACCACTTTA 909 TYK2 NM_003331 4507748 7297 D-003182-06 GCATCCACATTGCACATAA 910 TYK2 NM_003331 4507748 7297 D-003182-07 TCAAATACCTAGCCACACT 911 TYK2 NM_003331 4507748 7297 D-003182-08 CAATCTTGCTGACGTCTTG 912 TYRO3 TYRO3 NM_006293 27597077 7301 D-003183-05 GGTAGAAGGTGTGCCATTT 913 TYRO3 NM_006293 27597077 7301 D-003183-06 ACGCTGAGATTTACAACTA 914 TYRO3 NM_006293 27597077 7301 D-003183-07 GGATGGCTCCTTTGTGAAA 915 TYRO3 NM_006293 27597077 7301 D-003183-08 GAGAGGAACTACGAAGATC 916 YES1 YES1 NM_005433 21071041 7525 D-003184-05 GAAGGACCCTGATGAAAGA 917 YES1 NM_005433 21071041 7525 D-003184-06 TAAGAAGGGTGAAAGATTT 918 YES1 NM_005433 21071041 7525 D-003184-07 TCAAGAAGCTCAGATAATG 919 YES1 NM_005433 21071041 7525 D-003184-08 CAGAATCCCTCCATGAATT 920

TABLE VIII Gene Locus SEQ. ID Name Acc# Gl Link Duplex # Full Sequence NO. APC2 APC2 NM_013366 7549800 29882 D-003200-05 GCAAGGACCTCTTCATCAA 921 APC2 NM_013366 7549800 29882 D-003200-06 GAGAAGAAGTCCACACTAT 922 APC2 NM_013366 7549800 29882 D-003200-07 GGAATGCCATCTCCCAATG 923 APC2 NM_013366 7549800 29882 D-003200-09 CAACACGTGTGACATCATC 924 ATM ATM NM_000051 20336202 472 D-003201-05 GCAAGCAGCTGAAACAAAT 925 ATM NM_000051 20336202 472 D-003201-06 GAATGTTGCTTTCTGAATT 926 ATM NM_000051 20336202 472 D-003201-07 GACCTGAAGTCTTATTTAA 927 ATM NM_000051 20336202 472 D-003201-08 AGACAGAATTCCCAAATAA 928 ATR ATR NM_001184 20143978 545 D-003202-05 GAACAACACTGCTGGTTTG 929 ATR NM_001184 20143978 545 D-003202-06 GAAGTCATCTGTTCATTAT 930 ATR NM_001184 20143978 545 D-003202-07 GAAATAAGGTAGACTCAAT 931 ATR NM_001184 20143978 545 D-003202-08 CAACATAAATCCAAGAAGA 932 BTAK BTAK NM_003600 3213196 6790 D-003545-04 CAAAGAATCAGCTAGCAAA 933 BTAK NM_003600 3213196 6790 D-003545-05 GAAGAGAGTTATTCATAGA 934 BTAK NM_003600 3213196 6790 D-003545-07 CAAATGCCCTGTCTTACTG 935 BTAK NM_003600 3213196 6790 D-003545-09 TCTCGTGACTCAGCAAATT 936 CCNA1 CCNA1 NM_003914 16306528 890 D-003204-05 GAACCTGGCTAAGTACGTA 937 CCNA1 NM_003914 16306528 890 D-003204-06 GCAGATCCATTCTTGAAAT 938 CCNA1 NM_003914 16306528 890 D-003204-07 TCACAAGAATCAGGTGTTA 939 CCNA1 NM_003914 16306528 890 D-003204-08 CATAAAGCGTACCTTGATA 940 CCNA2 CCNA2 NM_001237 16950653 890 D-003205-05 GCTGTGAACTACATTGATA 941 CCNA2 NM_001237 16950653 890 D-003205-06 GATGATACCTACACCAAGA 942 CCNA2 NM_001237 16950653 890 D-003205-07 GCTGTTAGCCTCAAAGTTT 943 CCNA2 NM_001237 16950653 890 D-003205-08 AAGCTGGCCTGAATCATTA 944 CCNB1 CCNB1 NM_031966 14327895 891 D-003206-05 CAACATTACCTGTCATATA 945 CCNB1 NM_031966 14327895 891 D-003206-06 CCAAATACCTGATGGAACT 946 CCNB1 NM_031966 14327895 891 D-003206-07 GAAATGTACCCTCCAGAAA 947 CCNB1 NM_031966 14327895 891 D-003206-08 GCACCTGGCTAAGAATGTA 948 CCNB2 CCNB2 NM_004701 10938017 9133 D-003207-05 CAACAAATGTCAACAAACA 949 CCNB2 NM_004701 10938017 9133 D-003207-06 GCAGCAAACTCCTGAAGAT 950 CCNB2 NM_004701 10938017 9133 D-003207-07 CCAGTGATTTGGAGAATAT 951 CCNB2 NM_004701 10938017 9133 D-003207-08 GTGACTACGTTAAGGATAT 952 CCNB3 CCNB3 NM_033031 14719419 85417 D-003208-05 TGAACAAACTGCTGACTTT 953 CCNB3 NM_033031 14719419 85417 D-003208-06 GCTAGCTGCTGCCTCCTTA 954 CCNB3 NM_033031 14719419 85417 D-003208-07 CAACTCACCTCGTGTGGAT 955 CCNB3 NM_033031 14719419 85417 D-003208-08 GTGGATCTCTACCTAATGA 956 CCNC CCNC NM_005190 7382485 892 D-003209-05 GCAGAGCTCCCACTATTTG 957 CCNC NM_005190 7382485 892 D-003209-06 GGAGTAGTTTCAAATACAA 958 CCNC NM_005190 7382485 892 D-003209-07 GACCTTTGCTCCAGTATGT 959 CCNC NM_005190 7382485 892 D-003209-08 GAGATTCTATGCCAGGTAT 960 CCND1 CCND1 NM_053056 16950654 595 D-003210-05 TGAACAAGCTCAAGTGGAA 961 CCND1 NM_053056 16950654 595 D-003210-06 CCAGAGTGATCAAGTGTGA 962 CCND1 NM_053056 16950654 595 D-003210-07 GTTCGTGGCCTCTAAGATG 963 CCND1 NM_053056 16950654 595 D-003210-08 CCGAGAAGCTGTGCATCTA 964 CCND2 CCND2 NM_001759 16950656 894 D-003211-06 TGAATTACCTGGACCGTTT 965 CCND2 NM_001759 16950656 894 D-003211-07 CGGAGAAGCTGTGCATTTA 966 CCND2 NM_001759 16950656 894 D-003211-08 CTACAGACGTGCGGGATAT 967 CCND2 NM_001759 16950656 894 D-003211-09 CAACACAGACGTGGATTGT 968 CCND3 CCND3 NM_001760 16950657 896 D-003212-05 GGACCTGGCTGCTGTGATT 969 CCND3 NM_001760 16950657 896 D-003212-06 GATTATACCTTTGCCATGT 970 CCND3 NM_001760 16950657 896 D-003212-07 GACCAGCACTCCTACAGAT 971 CCND3 NM_001760 16950657 896 D-003212-08 TGCGGAAGATGCTGGCTTA 972 CCNE1 CCNE1 NM_001238 17318558 898 D-003213-05 GTACTGAGCTGGGCAAATA 973 CCNE1 NM_001238 17318558 898 D-003213-06 GGAAATCTATCCTCCAAAG 974 CCNE1 NM_001238 17318558 898 D-003213-07 GGAGGTGTGTGAAGTCTAT 975 CCNE1 NM_001238 17318558 898 D-003213-08 CTAAATGACTTACATGAAG 976 CCNE2 CCNE2 NM_057749 17318564 9134 D-003214-05 GGATGGAACTCATTATATT 977 CCNE2 NM_057749 17318564 9134 D-003214-06 GCAGATATGTTCATGACAA 978 CCNE2 NM_057749 17318564 9134 D-003214-07 CATAATATCCAGACACATA 979 CCNE2 NM_057749 17318564 9134 D-003214-08 TAAGAAAGCCTCAGGTTTG 980 CCNF CCNF NM_001761 4502620 899 D-003215-05 TCACAAAGCATCCATATTG 981 CCNF NM_001761 4502620 899 D-003215-06 GAAGTCATGTTTACAGTGT 982 CCNF NM_001761 4502620 899 D-003215-07 TAGCCTACCTCTACAATGA 983 CCNF NM_001761 4502620 899 D-003215-08 GCACCCGGTTTATCAGTAA 984 CCNG1 CCNG1 NM_004060 8670528 900 D-003216-05 GATAATGGCCTCAGAATGA 985 CCNG1 NM_004060 8670528 900 D-003216-06 GCACGGCAATTGAAGCATA 986 CCNG1 NM_004060 8670528 900 D-003216-07 GGAATAGAATGTCTTCAGA 987 CCNG1 NM_004060 8670528 900 D-003216-08 TAACTCACCTTCCAACAAT 988 CCNG2 CCNG2 NM_004354 4757935 901 D-003217-05 GGAGAGAGTTGGTTTCTAA 989 CCNG2 NM_004354 4757935 901 D-003217-06 GGTGAAACCTAAACATTTG 990 CCNG2 NM_004354 4757935 901 D-003217-07 GAAATACTGAGCCTTGATA 991 CCNG2 NM_004354 4757935 901 D-003217-08 TGCCAAAGTTGAAGATTTA 992 CCNH CCNH NM_001239 17738313 902 D-003218-05 GCTGATGACTTTCTTAATA 993 CCNH NM_001239 17738313 902 D-003218-06 CAACTTAATTTCCACCTTA 994 CCNH NM_001239 17738313 902 D-003218-07 ATACACACCTTCCCAAATT 995 CCNH NM_001239 17738313 902 D-003218-08 GCTATGAAGATGATGATTA 996 CCNI CCNI NM_006835 17738314 10983 D-003219-05 GCAAGCAGACCTCTACTAA 997 CCNI NM_006835 17738314 10983 D-003219-07 TGAGAGAATTCCAGTACTA 998 CCNI NM_006835 17738314 10983 D-003219-08 GGAATCAAACGGCTCTATA 999 CCNI NM_006835 17738314 10983 D-003219-09 GAATTGGGATCTTCACACA 1000 CCNT1 CCNT1 NM_001240 17978465 904 D-003220-05 TATCAACACTGCTATAGTA 1001 CCNT1 NM_001240 17978465 904 D-003220-06 GAACAAACGTCCTGGTGAT 1002 CCNT1 NM_001240 17978465 904 D-003220-07 GCACAAGACTCACCCATCT 1003 CCNT1 NM_001240 17978465 904 D-003220-08 GCACAGACTTCTTACTTCA 1004 CCNT2A CCNT2A NM_001241 17978467 905 D-003221-05 GCACAGACATCCTATTTCA 1005 CCNT2A NM_001241 17978467 905 D-003221-06 GCAGGGACCTTCTATATCA 1006 CCNT2A NM_001241 17978467 905 D-003221-07 GAACAGCTATATTCACAGA 1007 CCNT2A NM_001241 17978467 905 D-003221-09 TTATATAGCTGCCCAGGTA 1008 CCNT2B CCNT2B NM_058241 17978468 905 D-003222-05 GCACAGACATCCTATTTCA 1009 CCNT2B NM_058241 17978468 905 D-003222-06 GCAGGGACCTTCTATATCA 1010 CCNT2B NM_058241 17978468 905 D-003222-07 GAACAGCTATATTCACAGA 1011 CCNT2B NM_058241 17978468 905 D-003222-08 GGTGAAATGTACCCAGTTA 1012 CDC16 CDC16 NM_003903 14110370 8881 D-003223-05 GTAGATGGCTTGCAAGAGA 1013 CDC16 NM_003903 14110370 8881 D-003223-06 TAAAGTAGCTTCACTCTCT 1014 CDC16 NM_003903 14110370 8881 D-003223-07 GCTACAAGCTTACTTCTGT 1015 CDC16 NM_003903 14110370 8881 D-003223-08 TGGAAGAGCCCATCAATAA 1016 CDC2 CDC2 NM_033379 27886643 983 D-003552-01 GTACAGATCTCCAGAAGTA 1017 CDC2 NM_033379 27886643 983 D-003552-02 GATCAACTCTTCAGGATTT 1018 CDC2 NM_033379 27886643 983 D-003552-03 GGTTATATCTCATCTTTGA 1019 CDC2 NM_033379 27886643 983 D-003552-04 GAACTTCGTCATCCAAATA 1020 CDC20 CDC20 NM_001255 4557436 991 D-003225-05 GGGAATATATATCCTCTGT 1021 CDC20 NM_001255 4557436 991 D-003225-06 GAAACGGCTTCGAAATATG 1022 CDC20 NM_001255 4557436 991 D-003225-07 GAAGACCTGCCGTTACATT 1023 CDC20 NM_001255 4557436 991 D-003225-08 CACCAGTGATCGACACATT 1024 CDC25A CDC25A NM_001789 4502704 993 D-003226-05 GAAATTATGGCATCTGTTT 1025 CDC25A NM_001789 4502704 993 D-003226-06 TACAAGGAGTTCTTTATGA 1026 CDC25A NM_001789 4502704 993 D-003226-07 CCACGAGGACTTTAAAGAA 1027 CDC25A NM_001789 4502704 993 D-003226-08 TGGGAAACATCAGGATTTA 1028 CDC25B CDC25B NM_004358 11641416 994 D-003227-05 GCAGATACCCCTATGAATA 1029 CDC25B NM_004358 11641416 994 D-003227-06 CTAGGTCGCTTCTCTCTGA 1030 CDC25B NM_004358 11641416 994 D-003227-07 GAGAGCTGATTGGAGATTA 1031 CDC25B NM_004358 11641416 994 D-003227-08 AAAAGGACCTCGTCATGTA 1032 CDC25C CDC25C NM_001790 12408659 995 D-003228-05 GAGCAGAAGTGGCCTATAT 1033 CDC25C NM_001790 12408659 995 D-003228-06 CAGAAGAGATTTCAGATGA 1034 CDC25C NM_001790 12408659 995 D-003228-07 CCAGGGAGCCTTAAACTTA 1035 CDC25C NM_001790 12408659 995 D-003228-08 GAAACTTGGTGGACAGTGA 1036 CDC27 CDC27 NM_001256 16554576 996 D-003229-06 CATGCAAGCTGAAAGAATA 1037 CDC27 NM_001256 16554576 996 D-003229-07 CAACACAAGTACCTAATCA 1038 CDC27 NM_001256 16554576 996 D-003229-08 GGAGATGGATCCTAGTTAC 1039 CDC27 NM_001256 16554576 996 D-003229-09 GAAAAGCCATGATGATATT 1040 CDC34 CDC34 NM_004359 16357476 997 D-003230-05 GCTCAGACCTCTTCTACGA 1041 CDC34 NM_004359 16357476 997 D-003230-06 GGACGAGGGCGATCTATAC 1042 CDC34 NM_004359 16357476 997 D-003230-07 GATCGGGAGTACACAGACA 1043 CDC34 NM_004359 16357476 997 D-003230-08 TGAACGAGCCCAACACCTT 1044 CDC37 CDC37 NM_007065 16357478 11140 D-003231-05 GCGAGGAGACAGCCAATTA 1045 CDC37 NM_007065 16357478 11140 D-003231-06 CACAAGACCTTCGTGGAAA 1046 CDC37 NM_007065 16357478 11140 D-003231-07 ACAATCGTCATGCAATTTA 1047 CDC37 NM_007065 16357478 11140 D-003231-08 GAGGAGAAATGTGCACTCA 1048 CDC45L CDC45L NM_003504 34335230 8318 D-003232-05 GCACACGGATCTCCTTTGA 1049 CDC45L NM_003504 34335230 8318 D-003232-06 GCAAACACCTGCTCAAGTC 1050 CDC45L NM_003504 34335230 8318 D-003232-07 TGAAGAGTCTGCAAATAAA 1051 CDC45L NM_003504 34335230 8318 D-003232-08 GGACGTGGATGCTCTGTGT 1052 CDC6 CDC6 NM_001254 16357469 990 D-003233-05 GAACACAGCTGTCCCAGAT 1053 CDC6 NM_001254 16357469 990 D-003233-06 GAGCAGAGATGTCCACTGA 1054 CDC6 NM_001254 16357469 990 D-003233-07 GGAAATATCTTAGCTACTG 1055 CDC6 NM_001254 16357469 990 D-003233-08 GGACGAAGATTGGTATTTG 1056 CDC7 CDC7 NM_003503 11038647 8317 D-003234-05 GGAATGAGGTACCTGATGA 1057 CDC7 NM_003503 11038647 8317 D-003234-06 CAGGAAAGGTGTTCACAAA 1058 CDC7 NM_003503 11038647 8317 D-003234-07 CTACACAAATGCACAAATT 1059 CDC7 NM_003503 11038647 8317 D-003234-08 GTACGGGAATATATGCTTA 1060 CDK10 CDK10 NM_003674 32528262 8558 D-003235-05 GAACTGCTGTTGGGAACCA 1061 CDK10 NM_003674 32528262 8558 D-003235-06 GGAAGCAGCCCTACAACAA 1062 CDK10 NM_003674 32528262 8558 D-003235-07 GCACGCCCAGTGAGAACAT 1063 CDK10 NM_003674 32528262 8558 D-003235-08 GGAAGCAGCCCTACAACAA 1064 CDK2 CDK2 NM_001798 16936527 1017 D-003236-05 GAGCTTAACCATCCTAATA 1065 CDK2 NM_001798 16936527 1017 D-003236-06 GAGCTTAACCATCCTAATA 1066 CDK2 NM_001798 16936527 1017 D-003236-07 GTACCGAGCTCCTGAAATC 1067 CDK2 NM_001798 16936527 1017 D-003236-08 GAGAGGTGGTGGCGCTTAA 1068 CDK3 CDK3 NM_001258 4557438 1018 D-003237-05 GAGCATTGGTTGCATCTTT 1069 CDK3 NM_001258 4557438 1018 D-003237-06 GATCGGAGAGGGCACCTAT 1070 CDK3 NM_001258 4557438 1018 D-003237-07 GAAGCTCTATCTGGTGTTT 1071 CDK3 NM_001258 4557438 1018 D-003237-08 GCAGAGATGGTGACTCGAA 1072 CDK4 CDK4 NM_000075 456426 1019 D-003238-05 GCAGCACTCTTATCTACAT 1073 CDK4 NM_000075 456426 1019 D-003238-06 GGAGGAGGCCTTCCCATCA 1074 CDK4 NM_000075 456426 1019 D-003238-07 TCGAAAGCCTCTCTTCTGT 1075 CDK4 NM_000075 456426 1019 D-003238-08 GTACCGAGCTCCCGAAGTT 1076 CDK5 CDK5 NM_004935 4826674 1020 D-003239-05 TGACCAAGCTGCCAGACTA 1077 CDK5 NM_004935 4826674 1020 D-003239-06 GAGCTGAAATTGGCTGATT 1078 CDK5 NM_004935 4826674 1020 D-003239-07 CAACATCCCTGGTGAACGT 1079 CDK5 NM_004935 4826674 1020 D-003239-08 GGATTCCCGTCCGCTGTTA 1080 CDK6 CDK6 NM_001259 16950658 1021 D-003240-05 GCAAAGACCTACTTCTGAA 1081 CDK6 NM_001259 16950658 1021 D-003240-06 GAAGAAGACTGGCCTAGAG 1082 CDK6 NM_001259 16950658 1021 D-003240-07 GGTCTGGACTTTCTTCATT 1083 CDK6 NM_001259 16950658 1021 D-003240-08 TAACAGATATCGATGAACT 1084 CDK7 CDK7 NM_001799 16950659 1022 D-003241-05 GGACATAGATCAGAAGCTA 1085 CDK7 NM_001799 16950659 1022 D-003241-06 CAATAGAGCTTATACACAT 1086 CDK7 NM_001799 16950659 1022 D-003241-07 CATACAAGGCTTATTCTTA 1087 CDK7 NM_001799 16950659 1022 D-003241-08 GGAGACGACTTACTAGATC 1088 CDK8 CDK8 NM_001260 4502744 1024 D-003242-05 CCACAGTACTCACATCAGA 1089 CDK8 NM_001260 4502744 1024 D-003242-06 GCAATAACCACACTAATGG 1090 CDK8 NM_001260 4502744 1024 D-003242-07 GAAGAAAGTGAGAGTTGTT 1091 CDK8 NM_001260 4502744 1024 D-003242-08 GAACATGACCTCTGGCATA 1092 CDK9 CDK9 NM_0012611 7017983 1025 D-003243-05 GGCCAAACGTGGACAACTA 1093 CDK9 NM_0012611 7017983 1025 D-003243-06 TGACGTCCATGTTCGAGTA 1094 CDK9 NM_0012611 7017983 1025 D-003243-07 CCAACCAGACGGAGTTTGA 1095 CDK9 NM_0012611 7017983 1025 D-003243-08 GAAGGTGGCTCTGAAGAAG 1096 CDKN1C CDKN1C NM_000076 4557440 1028 D-003244-05 GACCAGAACCGCTGGGATT 1097 CDKN1C NM_000076 4557440 1028 D-003244-06 GGACCGAAGTGGACAGCGA 1098 CDKN1C NM_000076 4557440 1028 D-003244-08 GCAAGAGATCAGCGCCTGA 1099 CDKN1C NM_000076 4557440 1028 D-003244-09 CCGCTGGGATTACGACTTC 1100 CDKN2B CDKN2B NM_004936 17981693 1030 D-003245-05 GCGAGGAGAACAAGGGCAT 1101 CDKN2B NM_004936 17981693 1030 D-003245-06 CCAACGGAGTCAACCGTTT 1102 CDKN2B NM_004936 17981693 1030 D-003245-07 CGATCCAGGTCATGATGAT 1103 CDKN2B NM_004936 17981693 1030 D-003245-08 CCTGGAAGCCGGCGCGGAT 1104 CDKN2C CDKN2C NM_001262 17981697 1031 D-003246-05 GGACACCGCCTGTGATTTG 1105 CDKN2C NM_001262 17981697 1031 D-003246-06 GCCAGGAGACTGCTACTTA 1106 CDKN2C NM_001262 17981697 1031 D-003246-07 TGAAAGACCGAACTGGTTT 1107 CDKN2C NM_001262 17981697 1031 D-003246-08 GAACCTGCCCTTGCACTTG 1108 CDKN2D CDKN2D NM_001800 17981700 1032 D-003247-05 TGGCAGTTCAAGAGGGTCA 1109 CDKN2D NM_001800 17981700 1032 D-003247-06 CTCAGGACCTCGTGGACAT 1110 CDKN2D NM_001800 17981700 1032 D-003247-07 TGAAGGTCCTAGTGGAGCA 1111 CDKN2D NM_001800 17981700 1032 D-003247-08 AGACGGCGCTGCAGGTCAT 1112 CDT1 CDT1 NM_030928 19923847 81620 D-003248-05 CCAAGGAGGCACAGAAGCA 1113 CDT1 NM_030928 19923847 81620 D-003248-06 GCTTCAACGTGGATGAAGT 1114 CDT1 NM_030928 19923847 81620 D-003248-07 TCTCCGGGCCAGAAGATAA 1115 CDT1 NM_030928 19923847 81620 D-003248-08 GCGCAATGTTGGCCAGATC 1116 CENPA CENPA NM_001809 4585861 1058 D-003249-05 GCACACACCTCTTGATAAG 1117 CENPA NM_001809 4585861 1058 D-003249-06 GCAAGAGAAATATGTGTTA 1118 CENPA NM_001809 4585861 1058 D-003249-07 TTACATGCAGGCCGAGTTA 1119 CENPA NM_001809 4585861 1058 D-003249-08 GAGACAAGGTTGGCTAAAG 1120 CENPB CENPB NM_001810 26105977 1059 D-003250-05 GGACATAGCCGCCTGCTTT 1121 CENPB NM_001810 26105977 1059 D-003250-06 GCACGATCCTGAAGAACAA 1122 CENPB NM_001810 26105977 1059 D-003250-07 GGAGGAGGGTGATGTTGAT 1123 CENPB NM_001810 26105977 1059 D-003250-08 CCGAATGGCTGCAGAGTCT 1124 CENPC1 CENPC1 NM_001812 4502778 1060 D-003251-05 GCGAATAGATTATCAAGGA 1125 CENPC1 NM_001812 4502778 1060 D-003251-06 GAACAGAATCCATCACAAA 1126 CENPC1 NM_001812 4502778 1060 D-003251-07 CCATAAACCTCACCCAGTA 1127 CENPC1 NM_001812 4502778 1060 D-003251-08 CAAGAGAACACGTTTGAAA 1128 CENPE CENPE NM_001813 4502780 1062 D-003252-05 GAAGACAGCTCAAATAATA 1129 CENPE NM_001813 4502780 1062 D-003252-06 CAACAAAGCTACTAAATCA 1130 CENPE NM_001813 4502780 1062 D-003252-07 GGAAAGAAGTGCTACCATA 1131 CENPE NM_001813 4502780 1062 D-003252-08 GGAAAGAAATGACACAGTT 1132 CENPF CENPF NM_016343 14670380 1063 D-003253-05 GCGAATATCTGAATTAGAA 1133 CENPF NM_016343 14670380 1063 D-003253-06 GGAAATTAATGCATCCTTA 1134 CENPF NM_016343 14670380 1063 D-003253-07 GAGCGAGGCTGGTGGTTTA 1135 CENPF NM_016343 14670380 1063 D-003253-08 CAAGTCATCTTTCATCTAA 1136 CENPH CENPH NM_022909 21264590 64946 D-003254-05 GAAAGAAGAGATTGCAATT 1137 CENPH NM_022909 21264590 64946 D-003254-06 CAGAACAAATTATGCAAGA 1138 CENPH NM_022909 21264590 64946 D-003254-07 CTAGTGTGCTCATGGATAA 1139 CENPH NM_022909 21264590 64946 D-003254-08 GAAACACCTATTAGAGCTA 1140 CHEK1 CHEK1 NM_001274 20127419 1111 D-003255-05 CAAATTGGATGCAGACAAA 1141 CHEK1 NM_001274 20127419 1111 D-003255-06 GCAACAGTATTTCGGTATA 1142 CHEK1 NM_001274 20127419 1111 D-003255-07 GGACTTCTCTCCAGTAAAC 1143 CHEK1 NM_001274 20127419 1111 D-003255-08 AAAGATAGATGGTACAACA 1144 CHEK2 CHEK2 NM_007194 22209010 11200 D-003256-02 CTCTTACATTGCATACATA 1145 CHEK2 NM_007194 22209010 11200 D-003256-03 TAAACGCCTGAAAGAAGCT 1146 CHEK2 NM_007194 22209010 11200 D-003256-04 GCATAGGACTCAAGTGTCA 1147 CHEK2 NM_007194 22209010 11200 D-003256-05 GAAATTGCACTGTCACTAA 1148 CNK CNK NM_004073 4758015 1263 D-003257-05 GCGAGAAGATCCTAAATGA 1149 CNK NM_004073 4758015 1263 D-003257-07 GCAAGTGGGTTGACTACTC 1150 CNK NM_004073 4758015 1263 D-003257-08 GCACATCCGTTGGCCATCA 1151 CNK NM_004073 4758015 1263 D-003257-09 GACCTCAAGTTGGGAAATT 1152 CRI1 CRI1 NM_014335 7656937 23741 D-003258-05 GTGATGAGATTATTGATAG 1153 CRI1 NM_014335 7656937 23741 D-003258-06 GGACGAGGGCGAGGAATTT 1154 CRI1 NM_014335 7656937 23741 D-003258-07 GGAAACGGAGCCTTGCTAA 1155 CRI1 NM_014335 7656937 23741 D-003258-08 TCAATCGTCTGACCGAAGA 1156 E2F1 E2F1 NM_005225 12669910 1869 D-003259-05 GAACAGGGCCACTGACTCT 1157 E2F1 NM_005225 12669910 1869 D-003259-06 TGGACCACCTGATGAATAT 1158 E2F1 NM_005225 12669910 1869 D-003259-07 CCCAGGAGGTCACTTCTGA 1159 E2F1 NM_005225 12669910 1869 D-003259-08 GGCTGGACCTGGAAACTGA 1160 E2F2 E2F2 NM_004091 34485718 1870 D-003260-05 GGGAGAAGACTCGGTATGA 1161 E2F2 NM_004091 34485718 1870 D-003260-06 GAGGACAACCTGCAGATAT 1162 E2F2 NM_004091 34485718 1870 D-003260-07 TGAAGGAGCTGATGAACAC 1163 E2F2 NM_004091 34485718 1870 D-003260-08 CCAAGAAGTTCA1TTACCT 1164 E2F3 E2F3 NM_001949 12669913 1871 D-003261-05 GAAATTAGATGAACTGATC 1165 E2F3 NM_001949 12669913 1871 D-003261-06 TGAAGTGCCTGACTCAATA 1166 E2F3 NM_001949 12669913 1871 D-003261-07 GAACAAGGCAGCAGAAGTG 1167 E2F3 NM_001949 12669913 1871 D-003261-08 GAAACACACAGTCCAATGA 1168 E2F4 E2F4 NM_001950 12669914 1874 D-003262-05 GGAGATTGCTGACAAACTG 1169 E2F4 NM_001950 12669914 1874 D-003262-06 GAAGGTATCGGGCTAATCG 1170 E2F4 NM_001950 12669914 1874 D-003262-07 GTGCAGAAGTCCAGGGAAT 1171 E2F4 NM_001950 12669914 1874 D-003262-08 GGACAGTGGTGAGCTCAGT 1172 E2F5 E2F5 NM_001951 12669916 1875 D-003263-05 GCAGATGACTACAACTTTA 1173 E2F5 NM_001951 12669916 1875 D-003263-06 GACATCAGCTACAGATATA 1174 E2F5 NM_001951 12669916 1875 D-003263-07 CAACATGTCTCTGAAAGAA 1175 E2F5 NM_001951 12669916 1875 D-003263-08 GAAGACATCTGTAATTGCT 1176 E2F6 E2F6 NM_001952 12669917 1876 D-003264-05 TAAACAAGGTTGCAACGAA 1177 E2F6 NM_001952 12669917 1876 D-003264-06 TAGCATATGTGACCTATCA 1178 E2F6 NM_001952 12669917 1876 D-003264-07 GAAACCAGATTGGATGTTC 1179 E2F6 NM_001952 12669917 1876 D-003264-09 GGAACTTTCTGACTTATCA 1180 FOS FOS NM_005252 6552332 2353 D-003265-05 GGGATAGCCTCTCTTACTA 1181 FOS NM_005252 6552332 2353 D-003265-06 GAACAGTTATCTCCAGAAG 1182 FOS NM_005252 6552332 2353 D-003265-07 GGAGACAGACCAACTAGAA 1183 FOS NM_005252 6552332 2353 D-003265-08 AGACCGAGCCCTTTGATGA 1184 HIPK2 HIPK2 NM_022740 13430859 28996 D-003266-06 GAGAATCACTCCAATCGAA 1185 HIPK2 NM_022740 13430859 28996 D-003266-07 AGACAGGGATTAAGTCAAA 1186 HIPK2 NM_022740 13430859 28996 D-003266-08 GGACAAAGACAACTAGGTT 1187 HIPK2 NM_022740 13430859 28996 D-003266-09 GCACACACGTCAAATCATG 1188 HUS1 HUS1 NM_004507 31077213 3364 D-003267-05 ACAAAGGCCTTATGCAATA 1189 HUS1 NM_004507 31077213 3364 D-003267-06 GAAGTGCACATAGATATTA 1190 HUS1 NM_004507 31077213 3364 D-003267-07 AAGCTTAACTTCATCCTTT 1191 HUS1 NM_004507 31077213 3364 D-003267-08 GAACTTCTTCAACGAATTT 1192 JUN JUN NM_002228 7710122 3725 D-003268-05 TGGAAACGACCTTCTATGA 1193 JUN NM_002228 7710122 3725 D-003268-06 GAACTGCACAGCCAGAACA 1194 JUN NM_002228 7710122 3725 D-003268-07 GAGCTGGAGCGCCTGATAA 1195 JUN NM_002228 7710122 3725 D-003268-08 TAACGCAGCAGTTGCAAAC 1196 JUNB JUNB NM_002229 4504808 3726 D-003269-05 GCATCAAAGTGGAGCGCAA 1197 JUNB NM_002229 4504808 3726 D-003269-06 TGGAAGACCAAGAGCGCAT 1198 JUNB NM_002229 4504808 3726 D-003269-07 CATACACAGCTACGGGATA 1199 JUNB NM_002229 4504808 3726 D-003269-08 CCATCAACATGGAAGACCA 1200 LOC51053 LOC51053 NM_015895 20127542 51053 D-003270-05 GGAGAAAGGCGCTGTATGA 1201 LOC51053 NM_015895 20127542 51053 D-003270-06 GAATAGTTCTGTCCCAAGA 1202 LOC51053 NM_015895 20127542 51053 D-003270-07 GAACATGTACAGTATATGG 1203 LOC51053 NM_015895 20127542 51053 D-003270-08 GCAGAAACAAGAAGAAATC 1204 MAD2L1 MAD2L1 NM_002358 6466452 4085 D-003271-05 GAAAGATGGCAGTTTGATA 1205 MAD2L1 NM_002358 6466452 4085 D-003271-06 TAAATAATGTGGTGGAACA 1206 MAD2L1 NM_002358 6466452 4085 D-003271-07 GAAATCCGTTCAGTGATCA 1207 MAD2L1 NM_002358 6466452 4085 D-003271-08 TTACTCGAGTGCAGAAATA 1208 MAD2L2 MAD2L2 NM_006341 6006019 10459 D-003272-05 GGAAGAGCGCGCTCATAAA 1209 MAD2L2 NM_006341 6006019 10459 D-003272-06 TGGAAGAGCGCGCTCATAA 1210 MAD2L2 NM_006341 6006019 10459 D-003272-07 AGCCACTCCTGGAGAAGAA 1211 MAD2L2 NM_006341 6006019 10459 D-003272-08 TGGAGAAATTCGTCTTTGA 1212 MCM2 MCM2 NM_004526 33356546 4171 D-003273-05 GAAGATCTTTGCCAGCATT 1213 MCM2 NM_004526 33356546 4171 D-003273-06 GGATAAGGCTCGTCAGATC 1214 MCM2 NM_004526 33356546 4171 D-003273-07 CAGAGCAGGTGACATATCA 1215 MCM2 NM_004526 33356546 4171 D-003273-08 GCCGTGGGCTCCTGTATGA 1216 MCM3 MCM3 NM_002388 33356548 4172 D-003274-05 GGACATCAATATTCTTCTA 1217 MCM3 NM_002388 33356548 4172 D-003274-06 GCCAGGACATCTCCAGTTA 1218 MCM3 NM_002388 33356548 4172 D-003274-07 GCAGGTATGACCAGTATAA 1219 MCM3 NM_002388 33356548 4172 D-003274-08 GGAAATGCCTCAAGTACAC 1220 MCM4 MCM4 XM_030274 22047061 4173 D-003275-05 GGACATATCTATTCTTACT 1221 MCM4 XM_030274 22047061 4173 D-003275-06 GATGTTAGTTCACCACTGA 1222 MCM4 XM_030274 22047061 4173 D-003275-07 CCAGCTGCCTCATACTTTA 1223 MCM4 XM_030274 22047061 4173 D-003275-08 GAAAGTACAAGATCGGTAT 1224 MCM5 MCM5 NM_006739 23510447 4174 D-003276-05 GAAGATCCCTGGCATCATC 1225 MCM5 NM_006739 23510447 4174 D-003276-06 GAACAGGGTTACCATCATG 1226 MCM5 NM_006739 23510447 4174 D-003276-07 GGACAACATTGACTTCATG 1227 MCM5 NM_006739 23510447 4174 D-003276-08 CCAAGGAGGTAGCTGATGA 1228 MCM6 MCM6 NM_005915 33469920 4175 D-003277-05 GGAAAGAGCTCAGAGATGA 1229 MCM6 NM_005915 33469920 4175 D-003277-06 GAGCAGCGATGGAGAAATT 1230 MCM6 NM_005915 33469920 4175 D-003277-07 GGAAACACCTGATGTCAAT 1231 MCM6 NM_005915 33469920 4175 D-003277-08 CCAAACATCTGCCGAAATC 1232 MCM7 MCM7 NM_005916 33469967 4176 D-003278-05 GGAAATATCCCTCGTAGTA 1233 MCM7 NM_005916 33469967 4176 D-003278-06 GGAAGAAGCAGTTCAAGTA 1234 MCM7 NM_005916 33469967 4176 D-003278-07 CAACAAGCCTCGTGTGATC 1235 MCM7 NM_005916 33469967 4176 D-003278-08 GGAGAGAACACAAGGATTG 1236 MDM2 MDM2 NM_002392 4505136 4193 D-003279-05 GGAGATATGTTGTGAAAGA 1237 MDM2 NM_002392 4505136 4193 D-003279-06 CCACAAATCTGATAGTATT 1238 MDM2 NM_002392 4505136 4193 D-003279-07 GATGAGGTATATCAAGTTA 1239 MDM2 NM_002392 4505136 4193 D-003279-08 GGAAGAAACCCAAGACAAA 1240 MK167 MK167 NM_002417 19923216 4288 D-003280-05 GCACAAAGCTTGGTTATAA 1241 MK167 NM_002417 19923216 4288 D-003280-06 CCTAAGACCTGAACTATTT 1242 MK167 NM_002417 19923216 4288 D-003280-07 CAAAGAGGAACACAAATTA 1243 MK167 NM_002417 19923216 4288 D-003280-08 GTAAATGGGTCTGTTATTG 1244 MNAT1 MNAT1 NM_002431 4505224 4331 D-003281-05 GGAAGAAGCTTTAGAAGTG 1245 MNAT1 NM_002431 4505224 4331 D-003281-06 TAGATGAGCTGGAGAGTTC 1246 MNAT1 NM_002431 4505224 4331 D-003281-07 GGACCTTGCTGGAGGCTAT 1247 MNAT1 NM_002431 4505224 4331 D-003281 -08 GCAGATAGAGACATATGGA 1248 MYC MYC NM_002467 31543215 4609 D-003282-05 CAGAGAAGCTGGCCTCCTA 1249 MYC NM_002467 31543215 4609 D-003282-06 GAAACGACGAGAACAGTTG 1250 MYC NM_002467 31543215 4609 D-003282-07 CGACGAGACCTTCATCAAA 1251 MYC NM_002467 31543215 4609 D-003282-08 CCACACATCAGCACAACTA 1252 ORC1L ORC1L NM_004153 31795543 4998 D-003283-05 GAACAGGAATTCCAAGACA 1253 ORC1L NM_004153 31795543 4998 D-003283-06 TAAGAAACGTGCTCGAGTA 1254 ORC1L NM_004153 31795543 4998 D-003283-07 GAGATCACCTCACCTTCTA 1255 ORC1L NM_004153 31795543 4998 D-003283-08 GCAGAGAGCCCTTCTTGGA 1256 ORC2L ORC2L NM_006190 32454751 4999 D-003284-05 GAAGAAACCTCCTATGAGA 1257 ORC2L NM_006190 32454751 4999 D-003284-06 GAAGGGAACTGATGGAGTA 1258 ORC2L NM_006190 32454751 4999 D-003284-07 GAAGAATGATCCTGAGATT 1259 ORC2L NM_006190 32454751 4999 D-003284-08 GAAGAGATGTTCAAGAATC 1260 ORC3L ORC3L NM_012381 32483366 23595 D-003285-05 GGACTGCTGTGTAGATATA 1261 ORC3L NM_012381 32483366 23595 D-003285-06 GAACTGATGACCATACTTG 1262 ORC3L NM_012381 32483366 23595 D-003285-07 AAAGATCTCTCTGCCAATA 1263 ORC3L NM_012381 32483366 23595 D-003285-08 CAGCACAGCTAAGAGAATA 1264 ORC4L ORC4L NM_002552 32454749 5000 D-003286-06 GAAAGCACATTCCGTTTAT 1265 ORC4L NM_002552 32454749 5000 D-003286-07 TGAAAGAACTCATGGAAAT 1266 ORC4L NM_002552 32454749 5000 D-003286-08 GCTGAGAAGTGGAATGAAA 1267 ORC4L NM_002552 32454749 5000 D-003286-09 CCAGTGATCTTCATATTAG 1268 ORC5L ORC5L NM_002553 32454752 5001 D-003287-05 GAAATAACCTGTGAAACAT 1269 ORC5L NM_002553 32454752 5001 D-003287-06 CAGATTACCTCTCTAGTGA 1270 ORC5L NM_002553 32454752 5001 D-003287-07 GAACTTCCATATTACTCTA 1271 ORC5L NM_002553 32454752 5001 D-003287-08 GTATTCAGCTGATTTCTAT 1272 ORC6L ORC6L NM_014321 32454755 23594 D-003288-05 GAACATGGCTTCAAAGATA 1273 ORC6L NM_014321 32454755 23594 D-003288-06 GGACAGGGCTTATTTAATT 1274 ORC6L NM_014321 32454755 23594 D-003288-07 GAAAGAAGATAGTGGTTGA 1275 ORC6L NM_014321 32454755 23594 D-003288-08 TATCAGAGCTGTCTTAAAT 1276 PCNA PCNA NM_002592 33239449 5111 D-003289-05 GATCGAGGATGAAGAAGGA 1277 PCNA NM_002592 33239449 5111 D-003289-07 GCCGAGATCTCAGCCATAT 1278 PCNA NM_002592 33239449 5111 D-003289-09 GAGGCCTGCTGGGATATTA 1279 PCNA NM_002592 33239449 5111 D-003289-10 GTGGAGAACTTGGAAATGG 1280 PLK PLK NM_005030 21359872 5347 D-003290-05 CAACCAAAGTCGAATATGA 1281 PLK NM_005030 21359872 5347 D-003290-06 CAAGAAGAATGAATACAGT 1282 PLK NM_005030 21359872 5347 D-003290-07 GAAGATGTCCATGGAAATA 1283 PLK NM_005030 21359872 5347 D-003290-08 CAACACGCCTCATCCTCTA 1284 PIN1 PIN1 NM_006221 5453897 5300 D-003291-05 GGACCAAGGAGGAGGCCCT 1285 PIN1 NM_006221 5453897 5300 D-003291-06 CGTCCTGGCGGCAGGAGAA 1286 PIN1 NM_006221 5453897 5300 D-003291-07 CGGGAGAGGAGGACTTTGA 1287 PIN1 NM_006221 5453897 5300 D-003291-08 AGTCGGGAGAGGAGGACTT 1288 PIN1L PIN1L NM_006222 5453899 5301 D-003292-06 CGACCTGGCGGCAGGAAAT 1289 PIN1L NM_006222 5453899 5301 D-003292-07 AGGCAGGAGAGAAGGACTT 1290 PIN1L NM_006222 5453899 5301 D-003292-08 GCTACATCCAGAAGATCAA 1291 PIN1L NM_006222 5453899 5301 D-003292-09 GGACAGTGTTCACGGATTC 1292 RAD1 RAD1 NM_002853 19718797 5810 D-003293-05 GAAGATGGACAAATATGTT 1293 RAD1 NM_002853 19718797 5810 D-003293-06 GGAAGAGTCTGTTACTTTT 1294 RAD1 NM_002853 19718797 5810 D-003293-07 GATAACAGAGGCTTCCTTT 1295 RAD1 NM_002853 19718797 5810 D-003293-08 GCATTAGTCCTATCTTGTA 1296 RAD17 RAD17 NM_133338 19718783 5884 D-003294-05 GAATCAAGCTTCCATATGT 1297 RAD17 NM_133338 19718783 5884 D-003294-06 CAACAAAGCCCGAGGATAT 1298 RAD17 NM_133338 19718783 5884 D-003294-07 ACACATGCCTGGAGACTTA 1299 RAD17 NM_133338 19718783 5884 D-003294-08 CTACATAGATTTCTTCATG 1300 RAD9A RAD9A NM_004584 19924112 5883 D-003295-05 TCAGCAAACTTGAATCTTA 1301 RAD9A NM_004584 19924112 5883 D-003295-06 GACATTGACTCTTACATGA 1302 RAD9A NM_004584 19924112 5883 D-003295-08 GGAAACCACTATAGGCAAT 1303 RAD9A NM_004584 19924112 5883 D-003295-09 CGGACGACTTTGCCAATGA 1304 RB1 RB1 NM_000321 19924112 5925 D-003296-05 GAAAGGACATGTGAACTTA 1305 RB1 NM_000321 19924112 5925 D-003296-06 GAAGAAGTATGATGTATTG 1306 RB1 NM_000321 4506434 5925 D-003296-07 GAAATGACTTCTACTCGAA 1307 RB1 NM_000321 4506434 5925 D-003296-08 GGAGGGAACATCTATATTT 1308 RBBP2 RBBP2 NM_005056 4826967 5927 D-003297-05 CAAAGAAGCTGAATAAACT 1309 RBBP2 NM_005056 4826967 5927 D-003297-06 CAACACATATGGCGGATTT 1310 RBBP2 NM_005056 4826967 5927 D-003297-07 GGACAAACCTAGAAAGAAG 1311 RBBP2 NM_005056 4826967 5927 D-003297-08 GAAAGGCACTCTCTCTGTT 1312 RBL1 RBL1 NM_002895 34577078 5933 D-003298-05 CAAGAGAAGTTGTGGCATA 1313 RBL1 NM_002895 34577078 5933 D-003298-06 CAGCAGCACTCCATTTATA 1314 RBL1 NM_002895 34577078 5933 D-003298-07 ACAGAAAGGTCTATCATTT 1315 RBL1 NM_002895 34577078 5933 D-003298-08 GGACATAAAGTTACAATTC 1316 RBL2 RBL2 NM_005611 21361291 5934 D-003299-05 GAGCAGAGCTTAATCGAAT 1317 RBL2 NM_005611 21361291 5934 D-003299-06 GAGAATAGCCCTTGTGTGA 1318 RBL2 NM_005611 21361291 5934 D-003299-07 GGACTTAGTTTATGGAAAT 1319 RBL2 NM_005611 21361291 5934 D-003299-08 GAATTTAGATGAGCGGATA 1320 RBP1 RBP1 NM_002899 8400726 5947 D-003300-05 GAGACAAGCTCCAGTGTGT 1321 RBP1 NM_002899 8400726 5947 D-003300-06 GCAAGCAAGTATTCAAGAA 1322 RBP1 NM_002899 8400726 5947 D-003300-07 GCAGGACGGTGACCATATG 1323 RBP1 NM_002899 8400726 5947 D-003300-08 GCAAGTGCATGACAACAGT 1324 RPA3 RPA3 NM_002947 19923751 6119 D-003322-05 GGAAGTGGTTGGAAGAGTA 1325 RPA3 NM_002947 19923751 6119 D-003322-06 GAAGATAGCCATCCTTTTG 1326 RPA3 NM_002947 19923751 6119 D-003322-07 CATGCTAGCTCAATTCATC 1327 RPA3 NM_002947 19923751 6119 D-003322-08 GATCTTGGACTTTACAATG 1328 SKP1A SKP1A NM_006930 25777710 6500 D-003323-05 GGAGAGATATTTGAAGTTG 1329 SKP1A NM_006930 25777710 6500 D-003323-06 GGGAATGGATGATGAAGGA 1330 SKP1A NM_006930 25777710 6500 D-003323-07 CAAACAATCTGTGACTATT 1331 SKP1A NM_006930 25777710 6500 D-003323-08 TCAATTAAGTTGCAGAGTT 1332 SKP2 SKP2 NM_005983 16306594 6502 D-003324-05 CATCTAGACTTAAGTGATA 1333 SKP2 NM_005983 16306594 6502 D-003324-06 GAAATCAGATCTCTCTACT 1334 SKP2 NM_005983 16306594 6502 D-003324-07 CTAAAGGTCTCTGGTGTTT 1335 SKP2 NM_005983 16306594 6502 D-003324-08 GATGGTACCC1TCAACTGT 1336 SNK SNK NM_006622 5730054 10769 D-003325-05 GAAGACATCTACAAGCTTA 1337 SNK NM_006622 5730054 10769 D-003325-06 GAAATACCTTCATGAACAA 1338 SNK NM_006622 5730054 10769 D-003325-07 GAAGGTCAATGGCTCATAT 1339 SNK NM_006622 5730054 10769 D-003325-08 CCGGAGATCTCGCGGATTA 1340 STK12 STK12 NM_004217 4759177 9212 D-003326-07 CAGAAGAGCTGCACATTTG 1341 STK12 NM_004217 4759177 9212 D-003326-08 CCAAACTGCTCAGGCATAA 1342 STK12 NM_004217 4759177 9212 D-003326-09 ACGCGGCACTTCACAATTG 1343 STK12 NM_004217 4759177 9212 D-003326-10 TGGGACACCCGACATCTTA 1344 TFDP1 TFDP1 NM_007111 34147667 7027 D-003327-05 GGAAGCAGCTCTTGCCAAA 1345 TFDP1 NM_007111 34147667 7027 D-003327-06 GAGGAGACTTGAAAGAATA 1346 TFDP1 NM_007111 34147667 7027 D-003327-07 GAACTTAGAGGTGGAAAGA 1347 TFDP1 NM_007111 34147667 7027 D-003327-08 GCGAGAAGGTGCAGAGGAA 1348 TFDP2 TFDP2 NM_006286 5454111 7029 D-003328-05 GAAAGTGTGTGAGAAAGTT 1349 TFDP2 NM_006286 5454111 7029 D-003328-06 CACAGGACCTTCTTGGTTA 1350 TFDP2 NM_006286 5454111 7029 D-003328-07 CGAAATCCCTGGTGCCAAA 1351 TFDP2 NM_006286 5454111 7029 D-003328-08 TGAGATCCATGATGACATA 1352 TP53 TP53 NM_000546 8400737 7157 D-003329-05 GAGGTTGGCTCTGACTGTA 1353 TP53 NM_000546 8400737 7157 D-003329-06 CAGTCTACCTCCCGCCATA 1354 TP53 NM_000546 8400737 7157 D-003329-07 GCACAGAGGAAGAGAATCT 1355 TP53 NM_000546 8400737 7157 D-003329-08 GAAGAAACCACTGGATGGA 1356 TP63 TP63 NM_003722 31543817 8626 D-003330-05 CATCATGTCTGGACTATTT 1357 TP63 NM_003722 31543817 8626 D-003330-06 CAAACAAGATTGAGATTAG 1358 TP63 NM_003722 31543817 8626 D-003330-07 GCACACAGACAAATGAATT 1359 TP63 NM_003722 31543817 8626 D-003330-08 CGACAGTCTTGTACAATTT 1360 TP73 TP73 NM_005427 4885644 7161 D-003331-05 GCAAGCAGCCCATCAAGGA 1361 TP73 NM_005427 4885644 7161 D-003331-06 GAGACGAGGACACGTACTA 1362 TP73 NM_005427 4885644 7161 D-003331-07 CTGCAGAACCTGACCATTG 1363 TP73 NM_005427 4885644 7161 D-003331-08 GGCCATGCCTGTTTACAAG 1364 YWHAZ YWHAZ NM_003406 21735623 7534 D-003332-05 GCAAGGAGCTGAATTATCC 1365 YWHAZ NM_003406 21735623 7534 D-003332-06 TAAGAGATATCTGCAATGA 1366 YWHAZ NM_003406 21735623 7534 D-003332-07 GACGGAAGGTGCTGAGAAA 1367 YWHAZ NM_003406 21735623 7534 D-003332-08 AGAGCAAAGTCTTCTATTT 1368

TABLE IX Gene SEQ. ID Name Accession # GI# Duplex # Sequence NO. AR NM_000044 21322251 D-003400-01 GGAACTCGATCGTATCATT 1369 AR NM_000044 21322251 D-003400-02 CAAGGGAGGTTACACCAAA 1370 AR NM_000044 21322251 D-003400-03 TCAAGGAACTCGATCGTAT 1371 AR NM_000044 21322251 D-003400-04 GAAATGATTGCACTATTGA 1372 ESR1 NM_000125 4503602 D-003401-01 GAATGTGCCTGGCTAGAGA 1373 ESR1 NM_000125 4503602 D-003401-02 CATGAGAGCTGCCAACCTT 1374 ESR1 NM_000125 4503602 D-003401-03 AGAGAAAGATTGGCCAGTA 1375 ESR1 NM_000125 4503602 D-003401-04 CAAGGAGACTCGCTACTGT 1376 ESR2 NM_001437 10835012 D-003402-01 GAACATCTGCTCAACATGA 1377 ESR2 NM_001437 10835012 D-003402-02 GCACGGCTCCATATACATA 1378 ESR2 NM_001437 10835012 D-003402-03 CAAGAAGATTCCCGGCTTT 1379 ESR2 NM_001437 10835012 D-003402-04 GGAAATGCGTAGAAGGAAT 1380 ESRRA NM_004451 18860919 D-003403-01 GGCCTTCGCTGAGGACTTA 1381 ESRRA NM_004451 18860919 D-003403-02 TGAATGCACTGGTGTCTCA 1382 ESRRA NM_004451 18860919 D-003403-03 GCATTGAGCCTCTCTACAT 1383 ESRRA NM_004451 18860919 D-003403-04 CCAGACAGCGGGCAAAGTG 1384 ESRRB NM_004452 22035686 D-003404-01 TACCTGAGCTTACAAATTT 1385 ESRRB NM_004452 22035686 D-003404-02 GCACTTCTATAGCGTCAAA 1386 ESRRB NM_004452 22035686 D-003404-03 CAACTCCGATTCCATGTAC 1387 ESRRB NM_004452 22035686 D-003404-04 GGACTCGCCACCCATGTTT 1388 ESRRG NM_001438 4503604 D-003405-01 AAACAAAGATCGACACATT 1389 ESRRG NM_001438 4503604 D-003405-02 TCAGGAAACTGTATGATGA 1390 ESRRG NM_001438 4503604 D-003405-03 GAAGACCAGTCCAAATTAG 1391 ESRRG NM_001438 4503604 D-003405-04 ATGAAGCGCTGCAGGATTA 1392 HNF4A NM_000457 21361184 D-003406-01 CGACATCACTGGAGCATAT 1393 HNF4A NM_000457 21361184 D-003406-02 GAAGGAAGCCGTCCAGAAT 1394 HNF4A NM_000457 21361184 D-003406-03 CCAAGTACATCCCAGCTTT 1395 HNF4A NM_000457 21361184 D-003406-04 GGACATGGCCGACTACAGT 1396 HNF4G NM_004133 6631087 D-003407-01 GCACTGACATAAACGTTAA 1397 HNF4G NM_004133 6631087 D-003407-02 ACAAAGAGATCCATGATGT 1398 HNF4G NM_004133 6631087 D-003407-03 AGAGATCCATGATGTATAA 1399 HNF4G NM_004133 6631087 D-003407-04 AAATGAACGTGACAGAATA 1400 H5AJ2425 NM_017532 8923776 D-003408-01 GAATGAATCTACACCTTTG 1401 H5AJ2425 NM_017532 8923776 D-003408-02 GGAAATACGTGGAGACACT 1402 H5AJ2425 NM_017532 8923776 D-003408-03 CCAGATAACTACGGCGATA 1403 H5AJ2425 NM_017532 8923776 D-003408-04 TGGCGTACCTTCTCATTGA 1404 NROB1 NM_000475 5016089 D-003409-01 CAGCATGGATGATATGATG 1405 NROB1 NM_000475 5016089 D-003409-02 CTGCTGAGATTCATCAATG 1406 NROB1 NM_000475 5016089 D-003409-03 ACAGATTCATCGAACTTAA 1407 NROB1 NM_000475 5016089 D-003409-04 GAACGTGGCGCTCCTGTAC 1408 NROB2 NM_021969 13259502 D-003410-01 GAATATGCCTGCCTGAAAG 1409 NROB2 NM_021969 13259502 D-003410-02 GGAATATGCCTGCCTGAAA 1410 NROB2 NM_021969 13259502 D-003410-03 CGTAGCCGCTGCCTATGTA 1411 NROB2 NM_021969 13259502 D-003410-04 GCCATTCTCTACGCACTTC 1412 NR1D1 NM_021724 13430847 D-003411-01 CAACACAGGTGGCGTCATC 1413 NR1D1 NM_021724 13430847 D-003411-02 GGCATGGTGTTACTGTGTA 1414 NR1D1 NM_021724 13430847 D-003411-03 CAACATGCATTCCGAGAAG 1415 NR1D1 NM_021724 13430847 D-003411-04 GCGCTTTGCTTCGTTGTTC 1416 NR1H2 NM_007121 11321629 D-003412-01 GAACAGATCCGGAAGAAGA 1417 NR1H2 NM_007121 11321629 D-003412-02 GAAGAACAGATCCGGAAGA 1418 NR1H2 NM_007121 11321629 D-003412-03 CTAAGCAAGTGCCTGGTTT 1419 NR1H2 NM_007121 11321629 D-003412-04 GCTAACAGCGGCTCAAGAA 1420 NR1H3 NM_005693 5031892 D-003413-01 GAACAGATCCGCCTGAAGA 1421 NR1H3 NM_005693 5031892 D-003413-02 GGAGATAGTTGACTTTGCT 1422 NR1H3 NM_005693 5031892 D-003413-03 GAGTTTGCCTTGCTCATTG 1423 NR1H3 NM_005693 5031892 D-003413-04 TGACT1TGCTAAACAGCTA 1424 NR1H4 NM_005123 4826979 D-003414-01 CAAGTGACCTCGACAACAA 1425 NR1H4 NM_005123 4826979 D-003414-02 GAAAGAATTCGAAATAGTG 1426 NR1H4 NM_005123 4826979 D-003414-03 CAACAGACTCTTCTACATT 1427 NR1H4 NM_005123 4826979 D-003414-04 GAACCATACTCGCAATACA 1428 NR1I2 NM_003889 11863133 D-003415-01 GAACCATGCTGACTTTGTA 1429 NR1I2 NM_003889 11863133 D-003415-02 GATGGACGCTCAGATGAAA 1430 NR1I2 NM_003889 11863133 D-003415-03 CAACCTACATGTTCAAAGG 1431 NR1I2 NM_003889 11863133 D-003415-04 CAGGAGCAATTCGCCATTA 1432 NR1I3 NM_005122 4826660 D-003416-01 GGAAATCTGTCACATCGTA 1433 NR1I3 NM_005122 4826660 D-003416-02 TCGCAGACATCAACACTTT 1434 NR1I3 NM_005122 4826660 D-003416-03 CCTCTTCGCTACACAATTG 1435 NR1I3 NM_005122 4826660 D-003416-04 GAACAGTTTGTGCAGTTTA 1436 NR2C1 NM_003297 4507672 D-003417-01 TGACAGCACTTGATCATAA 1437 NR2C1 NM_003297 4507672 D-003417-02 GGAAGGAAGTGTACACCTA 1438 NR2C1 NM_003297 4507672 D-003417-03 GAGCACATCTTCAAACTAC 1439 NR2C1 NM_003297 4507672 D-003417-04 GAAGAAATTGCACATCAAA 1440 NR2C2 NM_003298 4507674 D-003418-01 GAACAACGGTGACACTTCA 1441 NR2C2 NM_003298 4507674 D-003418-02 CTGATGAGCTCCAACATAA 1442 NR2C2 NM_003298 4507674 D-003418-03 CAACCTAAGTGAATCTTTG 1443 NR2C2 NM_003298 4507674 D-003418-04 GAAGACACCTACCGATTGG 1444 NR2E1 NM_003269 21361108 D-003419-01 GATCATATCTGAAATACAG 1445 NR2E1 NM_003269 21361108 D-003419-02 CAAGACTGCTTTCAGATAT 1446 NR2E1 NM_003269 21361108 D-003419-03 GTTAGATGCTACTGAATTT 1447 NR2E1 NM_003269 21361108 D-003419-04 CAATGTATCTCTATGAAGT 1448 NR2E3 NM_014249 7657394 D-003420-01 GAGAAGCTCCTTTGTGATA 1449 NR2E3 NM_014249 7657394 D-003420-02 GAAGCACTATGGCATCTAT 1450 NR2E3 NM_014249 7657394 D-003420-03 GAAGGATCCTGAGCACGTA 1451 NR2E3 NM_014249 7657394 D-003420-04 GAAGCTCCTTTGTGATATG 1452 NR2F1 NM_005654 20127484 D-003421-01 GAAACTCTCATCCGCGATA 1453 NR2F1 NM_005654 20127484 D-003421-02 TCTCATCCGCGATATGTTA 1454 NR2F1 NM_005654 20127484 D-003421-03 CAAGAAGTGCCTCAAAGTG 1455 NR2F1 NM_005654 20127484 D-003421-04 GGAACTTAACTTACACATG 1456 NR2F2 NM_021005 14149745 D-003422-01 GTACCTGTCCGGATATATT 1457 NR2F2 NM_021005 14149745 D-003422-02 CCAACCAGCCGACGAGATT 1458 NR2F2 NM_021005 14149745 D-003422-03 ACTCGTACCTGTCCGGATA 1459 NR2F2 NM_021005 14149745 D-003422-04 GGCCGTATATGGCAATTCA 1460 NR2F6 NM_005234 20070198 D-003423-01 CGACGCCTGTGGCCTCTCA 1461 NR2F6 NM_005234 20070198 D-003423-02 CAGCCGGTGTCCGAACTGA 1462 NR2F6 NM_005234 20070198 D-003423-03 CAACCGTGACTGCCAGATC 1463 NR2F6 NM_005234 20070198 D-003423-04 GTACTGCCGTCTCAAGAAG 1464 NR3C1 NM_000176 4504132 D-003424-01 GAGGACAGATGTACCACTA 1465 NR3C1 NM_000176 4504132 D-003424-02 GATAAGACCATGAGTATTG 1466 NR3C1 NM_000176 4504132 D-003424-03 GAAGACGATTCATTCCTTT 1467 NR3C1 NM_000176 4504132 D-003424-04 GGACAGATGTACCACTATG 1468 NR3C2 NM_000901 4505198 D-003425-01 GCAAACAGATGATCCAAGT 1469 NR3C2 NM_000901 4505198 D-003425-02 CAGCTAAGATTTATCAGAA 1470 NR3C2 NM_000901 4505198 D-003425-03 GCACGAAAGTCAAAGAAGT 1471 NR3C2 NM_000901 4505198 D-003425-04 GGTATCCGGTCTTAGAATA 1472 NR4A1 NM_002135 21361341 D-003426-01 GAAGGAAGTTGTCCGAACA 1473 NR4A1 NM_002135 21361341 D-003426-02 CAGGAGAGTTTGACACCTT 1474 NR4A1 NM_002135 21361341 D-003426-03 CAGTGGCTCTGACTACTAT 1475 NR4A1 NM_002135 21361341 D-003426-04 GAAGGCCGCTGTGCTGTGT 1476 NR4A2 NM_006186 5453821 D-003427-01 GCAATGCGTTCGTGGCTTT 1477 NR4A2 NM_006186 5453821 D-003427-02 CGGCTACACAGGAGAGTTT 1478 NR4A2 NM_006186 5453821 D-003427-03 CCACGTGACTTTCAACAAT 1479 NR4A2 NM_006186 5453821 D-003427-04 GAATACAGCTCCGATTTCT 1480 NR4A3 NM_006981 11276070 D-003428-01 CAAAGAAGATCAGACATTA 1481 NR4A3 NM_006981 11276070 D-003428-02 GATCAGACATTACTTATTG 1482 NR4A3 NM_006981 11276070 D-003428-03 CCAGAGATCTTGATTATTC 1483 NR4A3 NM_006981 11276070 D-003428-04 GAAGTTGTCCGTACAGATA 1484 NR5A1 NM_004959 20070192 D-003429-01 GATTTGAAGTTCCTGAATA 1485 NR5A1 NM_004959 20070192 D-003429-02 GGAGCGAGCTGCTGGTGTT 1486 NR5A1 NM_004959 20070192 D-003429-03 GGAGGTGGCCGACCAGATG 1487 NR5A1 NM_004959 20070192 D-003429-04 CAACGTGCCTGAGCTCATC 1488 NR5A2 NM_003822 20070161 D-003430-01 CCAAACATATGGCCACTTT 1489 NR5A2 NM_003822 20070161 D-003430-02 TCAGAGAACTTAAGGTTGA 1490 NR5A2 NM_003822 20070161 D-003430-03 GGATCCATCTTCCTGGTTA 1491 NR5A2 NM_003822 20070161 D-003430-04 AAGAATACCTCTACTACAA 1492 NR6A1 NM_033334 15451847 D-003431-01 CAACGAACCTGTCTCATTT 1493 NR6A1 NM_033334 15451847 D-003431-02 GAAGAACTACACAGATTTA 1494 NR6A1 NM_033334 15451847 D-003431-03 GAAGATGGATACGCTGTGA 1495 NR6A1 NM_033334 15451847 D-003431-04 AAACGATACTGGTACATTT 1496 null D16815 2116671 D-003432-01 GAAGAATGATCGAATAGAT 1497 null D16815 2116671 D-003432-02 GAACATGGAGCAATATAAT 1498 null D16815 2116671 D-003432-03 GAGGAGCTCTTGGCCTTTA 1499 null D16815 2116671 D-003432-04 TAAACAACATGCACTCTGA 1500 PGR NM_000926 4505766 D-003433-01 GAGATGAGGTCAAGCTACA 1501 PGR NM_000926 4505766 D-003433-02 CAGCGTTTCTATCAACTTA 1502 PGR NM_000926 4505766 D-003433-03 AGATAACTCTCATTCAGTA 1503 PGR NM_000926 4505766 D-003433-04 GTAGTCAAGTGGTCTAAAT 1504 PPARA NM_005036 7549810 D-003434-01 TCACGGAGCTCACGGAATT 1505 PPARA NM_005036 7549810 D-003434-02 GAACATGACATAGAAGATT 1506 PPARA NM_005036 7549810 D-003434-03 GGATAGTTCTGGAAGCTTT 1507 PPARA NM_005036 7549810 D-003434-04 GACTCAAGCTGGTGTATGA 1508 PPARD NM_006238 5453939 D-003435-01 GAGCGCAGCTGCAAGATTC 1509 PPARD NM_006238 5453939 D-003435-02 GCATGAAGCTGGAGTACGA 1510 PPARD NM_006238 5453939 D-003435-03 GGAAGCAGTTGGTGAATGG 1511 PPARD NM_006238 5453939 D-003435-04 GCTGCAAGATTCAGAAGAA 1512 PPARG NM_138712 20336234 D-003436-01 AGACTCAGCTCTACAATAA 1513 PPARG NM_138712 20336234 D-003436-02 GATTGAAGCTTATCTATGA 1514 PPARG NM_138712 20336234 D-003436-03 AAGTAACTCTCCTCAAATA 1515 PPARG NM_138712 20336234 D-003436-04 GCATTTCTACTCCACATTA 1516 RARA NM_000964 4506418 D-003437-01 GACAAGAACTGCATCATCA 1517 RARA NM_000964 4506418 D-003437-02 GCAAATACACTACGAACAA 1518 RARA NM_000964 4506418 D-003437-03 GAACAACAGCTCAGAACAA 1519 RARA NM_000964 4506418 D-003437-04 GAGCAGCAGTTCTGAAGAG 1520 RARB NM_000965 14916493 D-003438-01 GCACACTGCTCAATCAATT 1521 RARB NM_000965 14916493 D-003438-02 GCAGAAGTATTCAGAAGAA 1522 RARB NM_000965 14916493 D-003438-03 GGAATGACAGGAACAAGAA 1523 RARB NM_000965 14916493 D-003438-04 GCACAGTCCTAGCATCTCA 1524 RARG NM_000966 21359851 D-003439-01 GAAATGACCGGAACAAGAA 1525 RARG NM_000966 21359851 D-003439-02 TAGAAGAGCTCATCACCAA 1526 RARG NM_000966 21359851 D-003439-03 CAAGGAAGCTGTGCGAAAT 1527 RARG NM_000966 21359851 D-003439-04 TCAGTGAGCTGGCTACCAA 1528 RORA NM_134261 19743902 D-003440-01 GGAAAGAGTTTATGTTCTA 1529 RORA NM_134261 19743902 D-003440-02 CAAGATCTGTGGAGACAAA 1530 RORA NM_134261 19743902 D-003440-03 GCACCTGACTGAAGATGAA 1531 RORA NM_134261 19743902 D-003440-04 CCGAGAAGATGGAATACTA 1532 RORB NM_006914 19743906 D-003441-01 GCACAGAACATCATTAAGT 1533 RORB NM_006914 19743906 D-003441-02 CCACACCTATGAAGAAATT 1534 RORB NM_006914 19743906 D-003441-03 GATCAAATTCTACTTCTGA 1535 RORB NM_006914 19743906 D-003441-04 TCAAACAGATAAAGCAAGA 1536 RORC NM_005060 19743908 D-003442-01 TAGAACAGCTGCAGTACAA 1537 RORC NM_005060 19743908 D-003442-02 TCACCGAGGCCATTCAGTA 1538 RORC NM_005060 19743908 D-003442-03 GAACAGCTGCAGTACAATC 1539 RORC NM_005060 19743908 D-003442-04 CCTCATGCCACCTTGAATA 1540 RXRA NM_002957 21536318 D-003443-01 TGACGGAGCTTGTGTCCAA 1541 RXRA NM_002957 21536318 D-003443-02 CAACAAGGACTGCCTGATT 1542 RXRA NM_002957 21536318 D-003443-03 GCAAGGACCTGACCTACAC 1543 RXRA NM_002957 21536318 D-003443-04 GCAAGGACCGGAACGAGAA 1544 RXRB NM_021976 21687229 D-003444-01 GCAAAGACCTTACATACTC 1545 RXRB NM_021976 21687229 D-003444-02 GCAATCATTCTGTTTAATC 1546 RXRB NM_021976 21687229 D-003444-03 TCACACCGATCCATTGATG 1547 RXRB NM_021976 21687229 D-003444-04 GCAAACGGCTATGTGCAAT 1548 RXRG NM_006917 21361386 D-003445-01 GGAAGGACCTCATCTACAC 1549 RXRG NM_006917 21361386 D-003445-02 GCGGATCTCTGGTTAAACA 1550 RXRG NM_006917 21361386 D-003445-03 GCGAGCCATTGTACTCTTT 1551 RXRG NM_006917 21361386 D-003445-04 GAGCCATTGTACTCTTTAA 1552 THRA NM_003250 20127451 D-003446-01 GGACAAAGACGAGCAGTGT 1553 THRA NM_003250 20127451 D-003446-02 GGAAACAGAGGCGGAAATT 1554 THRA NM_003250 20127451 D-003446-03 GTAAGCTGATTGAGCAGAA 1555 THRA NM_003250 20127451 D-003446-04 GAACCTCCATCCCACCTAT 1556 THRB NM_000461 10835122 D-003447-01 GAATGTCGCTTTAAGAAAT 1557 THRB NM_000461 10835122 D-003447-02 GAACAGTCGTCGCCACATC 1558 THRB NM_000461 10835122 D-003447-03 GGACAAGCACCAATAGTCA 1559 THRB NM_000461 10835122 D-003447-04 GTGGAAAGGTTGACTTGGA 1560 VDR NM_000376 4507882 D-003448-01 TGAAGAAGCTGAACTTGCA 1561 VDR NM_000376 4507882 D-003448-02 GCAACCAAGACTACAAGTA 1562 VDR NM_000376 4507882 D-003448-03 TCAATGCTATGACCTGTGA 1563 VDR NM_000376 4507882 D-003448-04 CCATTGAGGTCATCATGTT 1564

TABLE X Gene Symbol Sense SEQ. ID NO. ABCB1 GACCAUAAAUGUAAGGUUU 1565 UAGAAGAUCUGAUGUCAAA 1566 GAAAUGUUCACUUCAGUUA 1567 GAAGAUCGCUACUGAAGCA 1568 ABCC1 GGAAGCAACUGCAGAGACA 1569 GAUGACACCUCUCAACAAA 1570 UAAAGUUGCUCAUCAAGUU 1571 CAACGAGUCUGCCGAAGGA 1572 ABCG2 GCAGAUGCCUUCUUCGUUA 1573 AGGCAAAUCUUCGUUAUUA 1574 GGGAAGAAAUCUGGUCUAA 1575 UGACUCAUCCCAACAUUUA 1576 KCNH2 CCGACGUGCUGCCUGAGUA 1577 GAGAAGAGCAGCGACACUU 1578 GAUCAUAGCACCUAAGAUA 1579 GCUAUUUACUGCUCUUAUU 1580 UCACUGGGCUCCUUUAAUU 1581 GUGCGAGCCUUCUGAAUAU 1582 GCUAAGCUAUACUACUGUA 1583 UGACGGCGCUCUACUUCAC 1584 KCNH1 GAGAUGAAUUCCUUUGAAA 1585 GAAGAACGCAUGAAACGAA 1586 GAUAAAGACACGAUUGAAA 1587 GCUGAGAGGUCUAUUUAAA 1588 CLCA1 GAACAACAAUGGCUAUGAA 1589 GUACAUACCUGGCUGGAUU 1590 GAACAGCUCACAAGUAUAU 1591 GGAAACGUGUGUCUAUAUU 1592 SLC6A1 GGAGGUGGGAGGACAGUUA 1593 UCACAGCCCUGGUGGAUGA 1594 GAAGCUGGCUCCUAUGUUC 1595 GGUCAACACUACCAACAUG 1596 SLC6A2 GAACACAAGGUCAACAUUG 1597 AGAAGGAGCUGGCCUAGUG 1598 CGGAAACUCUUCACAUUUG 1599 CAACAAAUUUGACAACAAC 1600 SLC21A2 GUACAUCUCCAUCUUAUUU 1601 GGAAGUGGCUGAGUUAUUA 1602 GAAGGGAGGCUCAAUGUAA 1603 GAAGGAAGUGGCUGAGUUA 1604 SLC21A3 GUAGAAACAGGAGCUAUUA 1605 CAAGAUUACUGUCAAACAA 1606 GCACAAGAGUAUUUGGUAA 1607 GCAAAUGUCCCUUCUGUAU 1608 GCAUGACUCCUAUAUAAUA 1609 AAACAGCAAUUUCCCUUAA 1610 GAAAAUGCCUCUUCAGGAA 1611 SLC28A1 GUUCAUCGCUCUCCUCUUU 1612 GGAUCAAGCUGUUUCUGAA 1613 GGACUGCAGUUUGUACUUG 1614 GAGUGAAACUGACCUAUGG 1615 SLC29A1 GAACGCUGCUCCCGUGGAA 1616 GAAAGCCACUCUAUCAAAG 1617 GAAACCAGGUGCCUUCAGA 1618 CCUCACAGCUGUAUUCAUG 1619 SLC26A1 CCACGGAGCUGCUGGUCAU 1620 GGGUUGACAUCUUAUUUGA 1621 GCACGAGGGUCUCUGUGUU 1622 GGCCAUCGCCUACUCAUUG 1623 CAACACCCAUGGCAAUUAA 1624 GAGGAAAGAUCUUGCUGAU 1625 GAGCAAGCGUCCUCCAAAU 1626 GCAACACCCAUGGCAAUUA 1627 SLC26A2 CCAAAGAACUCAAUGAACA 1628 ACAAGAACCUUCAGACUAA 1629 GAAGGUAGAUAGAAGAAUG 1630 GUAUUGAACUGUACUGUAA 1631 SLC4A4 GCAAUUCUCUUCAUUUAUC 1632 GGAAAGAUGUCCACUGAAA 1633 GGACAAAGCCUUCUUCAAU 1634 GGAAUGGGAUCCAGCAAUU 1635 GLRA1 UGAAAGCCAUUGACAUUUG 1636 CAGACACGCUGGAGUUUAA 1637 CAAUAGCGCUUUCUGGUUU 1638 GCAGGUAGCAGAUGGACUA 1639 KLK1 UCAGAGUGCUGUCUUAUGU 1640 CAACUUGUUUGACGACGAA 1641 UGACAGAGCCUGCUGAUAC 1642 AGGCGGCUCUGUACCAUUU 1643 ADAM2 GAAACAUGCUGUGAUAUUG 1644 GCAGAUGUUUCCUUAUAUA 1645 CAACAGAGAUGCCAUGAUA 1646 GAAAGGCGCUACAUUGAGA 1647 XPNPEP1 GACCUGAGCUUCCCAACAA 1648 GCGACUGGCUCAACAAUUA 1649 GAGAUUGCGUGGCUAUUUA 1650 GACAGCAACUGGACACUUA 1651 GZMA GGAAGAGACUCGUGCAAUG 1652 GGAACCAUGUGCCAAGUUG 1653 GAAGUAACUCCUCAUUCAA 1654 GAACUCCUAUAGAUUUCUG 1655 CMKLR1 CAUAGAAGCUUUACCAAGA 1656 GAAUGGAGGAUGAAGAUUA 1657 GGUCAAUGCUCUAAGUGAA 1658 GAGAGGACUUCUAUGAAUG 1659 CLN3 CAUCAUGCCUUCUGAAUAA 1660 CAACAGCUCAUCACGAUUU 1661 GCAACAACUUCUCUUAUGU 1662 GGUCUUCGCUAGCAUCUCA 1663 CALCR GGACCUAGCUGUUGUAAAG 1664 GAAAGACCAUGCAUUUAAA 1665 GCAGGAAGAUGUAUGCUUU 1666 GAAUAAACCAGUAUCGUUA 1667 OXTR GGACCCAGAUAUCCAAAUA 1668 GCAAUACUAUCCUAACUGA 1669 GAAUAUAGAUUAGCGUUUG 1670 GAUGAGGCAUGACUACUAA 1671 EDG4 GCGAGUCUGUCCACUAUAC 1672 GAGAACGGCCACCCACUGA 1673 GAACGGCCACCCACUGAUG 1674 GGUCAAUGCUGCUGUGUAC 1675 EDG5 UCCAGGAACACUAUAAUUA 1676 GUGACCAUCUUCUCCAUCA 1677 CAUCCUCUGUUGCGCCAUU 1678 CCAACAAGGUCCAGGAACA 1679 EDG7 ACACUGAUACUGUCGAUGA 1680 AAUAGGAGCAACACUGAUA 1681 CAGCAGGAGUUACCUUGUU 1682 GGACACCCAUGAAGCUAAU 1683 PTCH GCACAGAACUCCACUCAAA 1684 GGACAGCAGUUCAUUGUUA 1685 GAGAAGAGGCUAUGUUUAA 1686 GGACAAACUUCGACCCUUU 1687 SMO UCGCUACCCUGCUGUUAUU 1688 GCUACAAGAACUACCGAUA 1689 CAAGAAAGCUUCCUUCAAC 1690 GAGAAGAAAUACAGUCAAU 1691 CASP3 CAAUAUAUCUGAAGAGCUA 1692 GAACUGGACUGUGGCAUUG 1693 GUGAGAAGAUGGUAUAUUU 1694 GAGGGUACUUUAAGACAUA 1695 CASP6 CAUGAGGUGUCAACUGUUA 1696 GAAGUGAAAUGCUUUAAUG 1697 AAAUAUGGCUCCUCCUUAG 1698 GCAAUCACAUUUAUGCAUA 1699 CAACAUAACUGAGGUGGAU 1700 CAUGGUACAUUCAAGAUUU 1701 CASP7 GAACUCUACUUCAGUCAAU 1704 GGGCAAAUGCAUCAUAAUA 1703 CAACAGAGGGAGUUUAAUA 1704 GAACAAAGCCACUGACUGA 1705 CASP8 GAAGUGAACUAUGAAGUAA 1706 CAACAAGGAUGACAAGAAA 1707 GGACAAAGUUUACCAAAUG 1708 GAGGGUCGAUCAUCUAUUA 1709 GAAUAUAGAGGGCUUAUGA 1710 CAACGACUAUGAAGAAUUC 1711 GAAGUGAGCAGAUCAGAAU 1712 GAGGAAAUCUCCAAAUGCA 1713 CASP9 CCAGGCAGCUGAUCAUAGA 1714 UCUCAGGUGUUGCCAAAUA 1715 GAACAGCUGUAAUCUAUGA 1716 CCACUGGUCUGUAGGGAUU 1717 DVL1 UCGUAAAGCUGUUGAUAUC 1718 GAGGAGAUCUUUGAUGACA 1719 GUAAAGCUGUUGAUAUCGA 1720 GAUCGUAAAGCUGUUGAUA 1721 DVL2 AGACGAAGGUGAUUUACCA 1722 UGUGAGAGGUACCUAGUCA 1723 GAAGAAAUUUCAGAUGACA 1724 UAAUAGGCAUUUCCUCUUU 1725 PTEN GUGAAGAUCUUGACCAAUG 1726 GAUCAGCAUACACAAAUUA 1727 GAAUGAACCUUCUGCAACA 1728 GGCGCUAUGUGUAUUAUUA 1729 PDK1 GUACAAAGCUGGUAUAUCC 1730 GAAAGACUCCCAGUGUAUA 1731 GGAAGUCCAUCUCAUCGAA 1732 CCAAAGACAUGACGACGUU 1733 PDK2 GUAAAGAGGAGACUGAAUG 1734 GGUCUGUGAUGGUCCCUAA 1735 CAAAGAUGCCUACGACAUG 1736 GGGCGAUGCCUGAGGGUUA 1737 PPP2CA UCACACAAGUUUAUGGUUU 1738 CAACAGCCGUGACCACUUU 1739 UAACCAAGCUGCAAUCAUG 1740 GAACUUGACGAUACUCUAA 1741 CTNNA1 GAAGAGAGGUCGUUCUAAG 1742 AAGCAGAUGUGCAUGAUUA 1743 UCUAAUAACUGCAGUGUUU 1744 GUAAAGGGCCCUCUAAUAA 1745 CTNNA2 GAAAGAAUAUGCCCAAGUU 1746 GAAGAAGAAUGCCACAAUG 1747 GCAGGAAGAUUAUGAUGUG 1748 AAAGAAAGCCCAUGUACUA 1749 HSPCA GGGAAAGAGCUGCAUAUUA 1750 GCUUAGAACUCUUUACUGA 1751 UAUAAGAGCUUGACCAAUG 1752 GCAGAUAUCUCUAUGAUUG 1753 DCTN2 CAACUCAUGUCCAAUACUG 1754 GGAAUGAGCCAGAUGUUUA 1755 GGAGACAGCUGUACGUUGU 1756 UCCAAGAGCUGACAACUGA 1757 CD2 GUAAGGAGAAGCAAUAUAA 1758 AAGAUGAGCUUUCCAUGUA 1759 GGACAUCUAUCUCAUCAUU 1760 GACAAGAGCCCACAGAGUA 1761 BAD GUACUUCCCUCAGGCCUAU 1762 GCUGUGCCUUGACUACGUA 1763 GUACUUCCCUCAGGCCUAU 1764 GGUCAGGUGCCUCGAGAUC 1765 SMAC CAGCGUAACUUCAUUCUUC 1766 UAACUUCAUUCUUCAGGUA 1767 CAGCUGCUCUUACCCAUUU 1768 GAUUGAAGCUAUUACUGAA 1769 UAGAAGAGCUCCGUCAGAA 1770 CCACAUAUGCGUUGAUUGA 1771 GCGCAGGGCUCUCUACCUA 1772 MAP3K5 GAACAGCCUUCAAAUCAAA 1773 GAUGUUCUCUACUAUGUUA 1774 GCAAAUACUGGAAGGAUUA 1775 CAGGAAAGCUCGUAAUUUA 1776 PVR CCACACGGCUGACCUCAUA 1777 CAGCAGAAUUCCUCUUAUA 1778 GCAGAAUUCCUCUUAUAAA 1779 GAUCGGGAUUUAUUUCUAU 1780 ERBB2 UGUGGGAGCUGAUGACUUU 1781 UCACAGAGAUCUUGAAAGG 1782 UGGAAGAGAUCACAGGUUA 1783 GCUCAUCGCUCACAACCAA 1784 SOS1 GAGCACCACUUCUAUGAUU 1785 CAAAGAAGCUGUUCAAUAU 1786 UGAAAGCCCUCCCUUAUUA 1787 GAAAUAGCAUGGAGAAGGA 1788 BRCA1 CCAUACAGCUUCAUAAAUA 1789 GAAGAGAACUUAUCUAGUG 1790 GAAGUGGGCUCCAGUAUUA 1791 GCAAGAUGCUGAUUCAUUA 1792 GAAGUGGGCUCCAGUAUUA 1793 GAACGGACACUGAAAUAUU 1794 GCAGAUAGUUCUACCAGUA 1795 CDKN1A GAACAAGGAGUCAGACAUU 1796 AAACUAGGCGGUUGAAUGA 1797 GAUGGAACUUCGACUUUGU 1798 GUAAACAGAUGGCACUUUG 1799 CDKN1B GGAAUGGACAUCCUGUAUA 1800 GGAGAAAGAUGUCAAACGU 1801 GAAUGGACAUCCUGUAUAA 1802 GUAAACAGCUCGAAUUAAG 1803 SLC2A4 CAGAUAGGCUCCGAAGAUG 1804 AGACUCAGCUCCAGAAUAC 1805 GAUCGGUUCUUUCAUCUUC 1806 CAGGAUCGGUUCUUUCAUC 1807 NOS2A CCAGAUAAGUGACAUAAGU 1808 UAAGUGACCUGCUUUGUAA 1809 GAAGAGAGAUUCCAUUGAA 1810 UGAAAGAGCUCAACAACAA 1811 FRAP1 GAGCAUGCCGUCAAUAAUA 1812 CAAGAGAACUCAUCAUAAG 1813 CCAAAGUGCUGCAGUACUA 1814 UAAGAAAGCUAUCCAGAUU 1815 FKBP1A GAAACAAGCCCUUUAAGUU 1816 GAAUUACUCUCCAAGUUGA 1817 CAGCACAAGUGGUAGGUUA 1818 GUUGAGGACUGAAUUACUC 1819 GAUGGCAGCUGUUUAAAUG 1820 GAGUAUCCUUUCAGUGUUA 1821 TNFRSF1A CAAAGGAACCUACUUGUAC 1822 GGAACCUACUUGUACAAUG 1823 GAACCUACUUGUACAAUGA 1824 GAGUGUGUCUCCUGUAGUA 1825 IL1R1 GGACAAGAAUCAAUGGAUA 1826 GAACAAGCCUCCAGGAUUC 1827 GGACUUGUGUGCCCUUAUA 1828 GAACACAAAGGCACUAUAA 1829 IRAK1 CGAAGAAAGUGAUGAAUUU 1830 GCUCUUUGCCCAUCUCUUU 1831 UGAAAGACCUGGUGGAAGA 1832 GCAAUUCAGUUUCUACAUC 1833 TRAF2 GAAGACAGAGUUAUUAAAC 1834 UCACGAAGACAGAGUUAUU 1835 AGACAGAGUUAUUAAACCA 1836 CACGAAGACAGAGUUAUUA 1837 GCUGAAGCCUGUCUGAUGU 1838 TRAF6 CAAAUGAUCUGAGGCAGUU 1839 GUUCAUAGUUUGAGCGUUA 1840 GGAGAAACCUGUUGUGAUU 1841 GGACAAAGUUGCUGAAAUC 1842 CAAAUGAUCUGAGGCAGUU 1843 GGAGAAACCUGUUGUGAUU 1844 GGACAAAGUUGCUGAAAUC 1845 GUUCAUAGUUUGAGCGUUA 1846 TRADD UGAAGCACCUUGAUCUUUG 1847 GGGCAGCGCAUACCUGUUU 1848 GAGGAGCGCUGUUUGAGUU 1849 GGACGAGGAGCGCUGUUUG 1850 GAGGAGCGCUGUUUGAGUU 1851 GGAUGUCUCUCUCCUCUUU 1852 GCUCACUCCUUUCUACUAA 1853 UGAAGCACCUUGAUCUUUG 1854 FADD GCACAGAUAUUUCCAUUUC 1855 GCAGUCCUCUUAUUCCUAA 1856 GAACUCAAGCUGCGUUUAU 1857 GGACGAAUUGAGAUAAUAU 1858 IKBKE UAAGAACACUGCUCAUGAA 1859 GAGGCAUCCUGAAGCAUUA 1860 GAAGGCGGCUGCAGAACUG 1861 GGAACAAGGAGAUCAUGUA 1862 IKBKG CUAUCGAGGUCGUUAAAUU 1863 GAAUGCAGCUGGAAGAUCU 1864 GCGGCGAGCUGGACUGUUU 1865 CCAGACCGAUGUGUAUUUA 1866 TNFRSF5 GGUCUCACCUCGCUAUGGU 1867 GAAAGCGAAUUCCUAGACA 1868 GCACAAACAAGACUGAUGU 1869 GAAGGGCACCUCAGAAACA 1870 UCUCCCAACUUGUAUUAAA 1871 RELA UCAAGUGUCUUCCAUCAUG 1872 UCAAGUGCCUUAAUAGUAG 1873 GGAGUACCCUGAGGCUAUA 1874 GAUGAGAUCUUCCUACUGU 1875 ARHA GAGCUGGGCUAAGUAAAUA 1876 GACCAAAGAUGGAGUGAGA 1877 GGAAGAAACUGGUGAUUGU 1878 GGCUGUAACUACUUUAUAA 1879 CDC42 GGACAUUUGUUUGCCAUUU 1880 GGAGAACCAUAUACUCUUG 1881 GAACCAAUGCUUUCUCAUG 1882 GAAGACCUGUUAUGUAGAG 1883 GAUCAAGAAUUGCAAUAUC 1884 GAAAAGGGGUGACCUAGUA 1885 UGACAAACCUUAUGGAAAA 1886 ROCK1 GGAAUGAGCUUCAGAUGCA 1887 GGACACAGCUGUAAGAUUG 1888 GACAAGAGAUUACAGAUAA 1889 GAAGAAACAUUCCCUAUUC 1890 PAK1 GAGGGUGGUUUAUGAUUAA 1891 CAACAAAGAACAAUCACUA 1892 GAAGAAAUAUACACGGUUU 1893 UACAUGAGCUUUACAGAUA 1894 PAK2 GGUAGGAGAUGAAUUGUUU 1895 AGAAGGAACUGAUCAUUAA 1896 CUACAGACCUCCAAUAUCA 1897 GAAACUGGCCAAACCGUUA 1898 PAK3 GAUUAUCGCUGCAAAGGAA 1899 GAGAGUGCCUGCAAGCUUU 1900 GACAAGAGGUGGCCAUAAA 1901 UUAAAUCGCUGUCUUGAGA 1902 PAK4 ACUAAGAGGUGAACAUGUA 1903 GAUCAUGAAUGUCCGAAGA 1904 GAUGAGACCCUACUACUGA 1905 CAGCAAAGGUGCCAAAGAU 1906 PAK6 UAAAGGCAGUUGUCCACUA 1907 GAAGGGACCUGCUUUCUUG 1908 GCAAAGACGUCCCUAAGAG 1909 CCAAUGGGCUGGCUGCAAA 1910 PAK7 GAGCACGGCUUUAAUAAGU 1911 CAAACUCCGUUAUGAUAUA 1912 GGAUAAAGUUGUCUGAUUU 1913 GGAAAUGCCUCCAUAAAUA 1914 HDAC1 GGACAUCGCUGUGAAUUGG 1915 AGAAAGAAGUCACCGAAGA 1916 GGACAAGGCCACCCAAUGA 1917 CCACAGCGAUGACUACAUU 1918 HDAC2 GCUGUUAAAUUAUGGCUUA 1919 GCAAAGAAAGCUAGAAUUG 1920 CAUCAGAGAGUCUUAUAUA 1921 CCAAUGAGUUGCCAUAUAA 1922 CREBBP GGCCAUAGCUUAAUUAAUC 1923 GCACAGCCGUUUACCAUGA 1924 GGACAGCCCUUUAGUCAAG 1925 GAACUGAUUCCUGAAAUAA 1926 BTRC CACAUAAACUCGUAUCUUA 1927 GAGAAGGCACUCAAGUUUA 1928 AGACAUAGUUUACAGAGAA 1929 GCAGAGAGAUUUCAUAACU 1930 RIPK2 GAACAUACCUGUAAAUCAU 1931 GGACAUCGACCUGUUAUUA 1932 UAAAUGAACUCCUACAUAG 1933 GGAAUUAUCUCUGAACAUA 1934 VAV1 GCAGAAAUACAUCUACUAA 1935 GCUAUGAGCUGUUCUUCAA 1936 CGACAAAGCUCUACUCAUC 1937 GCUCAACCCUGGAGACAUU 1938 VAV2 GGACAAGACUCGCAGAUUU 1939 GCUGAGCGCUUUGCAAUAA 1940 CAAGAAGUCUCACGGGAAA 1941 UCACAGAGGCCAAGAAAUU 1942 GRB2 UGGAAGCCAUCGCCAAAUA 432 CAUCAGUGCAUGACGUUUA 1943 UGAAUGAGCUGGUGGAUUA 1944 UGCCAAAACUUACCUAUAA 1945 PLCG1 GAGCUGCACUCCMUGAGA 1946 GAAACCAAGCCAUUAAUGA 1947 CCAAGGAGCUACUGACAUU 1948 AGAGAAACAUGGCCCAAUA 1949 ITGB1 CCACAGACAUUUACAUUAA 1950 GAAGGGAGUUUGCUAAAUU 1951 GAACAGAUCUGAUGAAUGA 1952 CAAGAGAGCUGAAGACUAU 1953 ITGA4 GCAUAUAUAUUCAGCAUUG 1954 CAACUUGACUGCAGUAUUG 1955 GAACUUAACUUUCCAUGUU 1956 GACAAGACCUGUAGUAAUU 1957 STAT1 AGAAAGAGCUUGACAGUAA 1958 GGAAGUAGUUCACAAAAUA 1959 UGAAGUAUCUGUAUCCAAA 1960 GAGCUUCACUCCCUUAGUU 1961 KRAS2 UAAGGACUCUGAAGAUGUA 1962 GACAAAGUGUGUAAUUAUG 1963 GCUCAGGACUUAGCAAGAA 1964 GAAACUGAAUACCUAAGAU 1965 GAAACUGAAUACCUAAGAU 1966 UAAGGACUCUGAAGAUGUA 1967 GACAAAGUGUGUAAUUAUG 1968 GCUCAGGACUUAGCAAGAA 1969 HRAS CCAUCCAGCUGAUCCAGAA 1970 GAACCCUCCUGAUGAGAGU 1971 GAGGACAUCCACCAGUACA 1972 BRAF GAUUAGAGACCAAGGAUUU 2410 CCACUGAUGUGUGUUAAUU 1973 CAAUAGAACCUGUCAAUAU 1974 GAAGACAGGAAUCGAAUGA 1975 ELK1 GAUGUGAGUAGAAGAGUUA 2411 GGAAGAAUUUGUACCAUUU 1976 GAACGACCUUUCUUUCUUU 1977 GGAGUCAUCUCUUCCUAUA 1978 RALGDS GGAGAAGCCUCACCUCUUG 1979 GCAGAAAGGACUCAAGAUU 1980 GAGAACAACUACUCAUUGA 1981 GAACUUCUCGUCACUGUAU 1982 PRKCA GGAUUGUUCUUUCUUCAUA 1983 GAAGGGUUCUCGUAUGUCA 1984 GAAGAAGGAUGUGGUGAUU 1985 GGACUGGGAUCGAACAACA 1986 MAP2K4 GGACAGAAGUGGAAAUAUU 1987 UCAAAGAGGUGAACAUUAA 1988 GACCAAAUCUCAGUUGUUU 1989 GGAGAAUGGUGCUGUUUAA 1990 MAP2K7 GAAGAGACCAAAGUAUAAU 1991 GAAGACCGGCCACGUCAUU 1992 GGAAGAGACCAAAGUAUAA 1993 GCAUUGAGAUUGACCAGAA 1994 UGAGAGAACGAGAAAGUUG 1995 GUGAAACCCUGUCUGCAUU 1996 GGAUCUCUCUCAACAACUA 1997 ACAACUAGGUGAACACAUA 1998 MAPK8 UCACAGUCCUGAAACGAUA 1999 GAUUGGAGAUUCUACAUUC 2000 GCUCAUGGAUGCAAAUCUU 2001 GAAGCUAAGCCGACCAUUU 2002 MAPK9 AAAGAGAGCUUAUCGUGAA 2003 GAUGAUAGGUUAGAAAUAG 2004 ACAAAGAAGUCAUGGAUUG 2005 GGAGCUGGAUCAUGAAAGA 2006 AIF1 GAAAAGGGAUGAUGGGAUU 2007 CCUAGACGAUCCCAAAUAU 2008 GAGCCAAACCAGGGAUUUA 2009 UGAAACGAAUGCUGGAGAA 2010 UCACUCACCCAGAGAAAUA 2011 CCAAGAAAGCUAUCUCUGA 2012 AGACUCACCUAGAGCUAAA 2013 BBC3 CCUGGAGGGUCCUGUACAA 2014 GAGCAAAUGAGCCAAACGU 2015 GGAGGGUCCUGUACAAUCU 2016 GACUUUCUCUGCACCAUGU 2017 BCL2L1 CCAGGGAGCUUGAAAGUUU 2018 AAAGUGCAGUUCAGUAAUA 2019 GAGAAUCACUAACCAGAGA 2020 GAGCCCAUCCCUAUUAUAA 2021 BCL2L11 GAGACGAGUUUAACGCUUA 2022 AAAGCAACCUUCUGAUGUA 2023 CCGAGAAGGUAGACAAUUG 2024 GCAAAGCAACCUUCUGAUG 2025 AGACAGAGCCACAAGGUAA 2026 GCAAGGAGGUUAGAGAAAU 2027 CAAGGAGGUUAGAGAAAUA 2028 UCUUACGACUGUUACGUUA 2029 BID GAAGACAUCAUCCGGAAUA 2030 CAACAGCGUUCCUAGAGAA 2031 GAAAUGGGAUGGACUGAAC 2032 ACGAUGAGCUGCAGACUGA 2033 BIRC2 GAAAGAAGCCUGCAUAUAA 2034 GAAAUUGACUCUACAUUGU 2035 ACAAAUAGCACUUAGGUUA 2036 GAAUACACCUGUGGUUAAA 2037 BIRC3 GGAGAUGCCUGCCAUUAAA 2038 UCAAUGAUCUUGUGUUAGA 2039 GAAAGAACAUGUAAAGUGU 2040 GAAGAAAGAACAUGUAAAG 2041 BIRC4 GUAGAUAGAUGGCAAUAUG 2042 GAGGAGGGCUAACUGAUUG 2043 GAGGAACCCUGCCAUGUAU 2044 GCACGGAUCUUUACUUUUG 2045 BIRC5 GGCGUAAGAUGAUGGAUUU 2046 GCAAAGGAAACCAACAAUA 2047 GCACAAAGCCAUUCUAAGU 2048 CAAAGGAAACCAACAAUAA 2049 BRCA1 CCAUACAGCUUCAUAAAUA 2050 GAAGAGAACUUAUCUAGUG 2051 GAAGUGGGCUCCAGUAUUA 2052 GCAAGAUGCUGAUUCAUUA 2053 CCAUACAGCUUCAUAAAUA 2054 CARD4 GAAAGUUAAUGUCAAGGAA 2055 GAGCAACACUGGCAUAACA 2056 UAACAGAGAUUUGCCUAAA 2057 GCGAAGAGCUGACCAAAUA 2058 CASP10 CAAAGGGUUUCUCUGUUUA 2059 GAAAUGACCUCCCUAAGUU 2060 GAAGGCAGCUGGUAUAUUC 2061 GACAUGAUCUUCCUUCUGA 2062 GCACUCUUCUGUUCCCUUA 2063 CASP2 GUAUUAAACUCUCCUUUGA 2064 GCAAGGAGAUGUCUGAAUA 2065 CAACUUCCCUGAUCUUUAA 2066 GCUCAAAGAUGUAAUGUAG 2067 CDKN1A GAACAAGGAGUCAGACAUU 2068 AAACUAGGCGGUUGAAUGA 2069 GAUGGAACUUCGACUUUGU 2070 GUAAACAGAUGGCACUUUG 2071 CFLAR GAUGUGUCCUCAUUAAUUU 2072 GAAGAGAGAUACAAGAUGA 2073 GAGCAUACCUGAAGAGAGA 2074 GCUAUGAAGUCCAGAAAUU 2075 CLK2 GUGAAUAUGUGAAAUAGUG 2076 AAAGCAUGCUAGAGUAUGA 2077 UUAAGAAUGUGGAGAAGUA 2078 GAUAACAAGCUGACACAUA 2079 CLSPN GGACGUAAUUGAUGAAGUA 2080 GCAGAUGGGUUCUUAAAUG 2081 CAAAUGAGGUUGAGGAAAU 2082 GGAAAUACCUGGAGGAUGA 2083 CSNK2A1 GAUCCACGUUUCAAUGAUA 2084 GCAUUUAGGUGGAGACUUC 2085 GAUGUACGAUUAUAGUUUG 2086 UGAAUUAGAUCCACGUUUC 2087 CTNNB1 GCACAAGAAUGGAUCACAA 2088 GCUGAAACAUGCAGUUGUA 2089 GUACGUACCAUGCAGAAUA 2090 GAACUUGCAUUGUGAUUGG 2091 CXCR4 GAAGCAUGACGGACAAGUA 2092 GAACAUUCCAGAGCGUGUA 2093 GUUCUUAGUUGCUGUAUGU 2094 CAUCAUGGUUGGCCUUAUC 2095 CXCR6 GGAACAAACUGGCAAAGCA 2096 GAUCAGAGCAGCAGUGAAA 2097 GGGCAAAACUGAAUUAUAA 2098 GAUCUCAGGUUCUCCUUGA 2099 DAXX CUACAGAUCUCCAAUGAAA 2100 GCUACAAGCUGGAGAAUGA 2101 GGAAACAGCUAUGUGGAAA 2102 GGAGUUGGAUCUCUCAGAA 2103 GAS41 GUAGUAAGCUAAACUGAAA 2104 GACAAUAUGUUCAAGAGAA 2105 GACAACAUCUCGUCAGCUA 2106 UAUAUGAUGUGUCCAGUAA 2107 GTSE1 CAAAGAAGCUCACUUACUG 2108 GAACAGCCCUAAAGUGGUU 2109 GAACAUGGAUGACCCUAAG 2110 GGGCAAAGCUAAAUCAAGU 2111 HDAC3 GGAAAGCGAUGUGGAGAUU 2112 CCAAGACCGUGGCCUAUUU 2113 AAAGCGAUGUGGAGAUUUA 2114 GUGAGGAGCUUCCCUAUAG 2115 HDAC5 GAAUUCCUCUUGUCGAAGU 2116 GUUAUUAGCACCUUUAAGA 2117 GGAGGGAGGCCAUGACUUG 2118 CAGGAGAGCUCAAGAAUGG 2119 GGAUAUGGAUUUCAGUUAA 2120 GGAAGUCGGUGCCUUGGUU 2121 GGAAGGAGAGGACUGGUUU 2122 HEC GCAGAUACUUGCACGGUUU 2123 GAGUAGAACUAGAAUGUGA 2124 GCGAAUAAAUCAUGAAAGA 2125 GAAGAUGGAAUUAUGCAUA 2126 HIST1H2 GGCAAUGCGUCUCGCGAUA 2127 AA GAUCCGCAAUGAUGAGGAA 2128 GCAAUGCGUCUCGCGAUAA 2129 GAGGAACUCAAUAAGCUUU 2130 LMNB1 AAUAGAAGCUGUGCAAUUA 2131 CAACUGACCUCAUCUGGAA 2132 GAAGGAAUCUGAUCUUAAU 2133 GGGAAGGGUUUCUCUAUUA 2134 LMNB2 GGAGGUUCAUUGAGAAUUG 2134 GGCAAUAGCUCACCGUUUA 2135 CAAAUACGCUUAGCUGUGU 2136 GGAGAUCGCCUACAAGUUC 2137 MYB GCAGAAACACUCCAAUUUA 2138 GUAAAUACGUGAAUGCAUU 2139 GCACUGAACUUUUGAGAUA 2140 GAAGAACAGUCAUUUGAUG 2141 MYT1 GAGGUGAGCUGUUAAAUCA 2142 GCAGGGUGAUUUCCUAAUA 2143 GGGAGAAGAUAUUUAAUUG 2144 CAACUUCUCUCCUGAACUU 2145 NFKBIB GGACACGGCACUGCACUUG 2146 GCACUUGGCUGUGAUUCAU 2148 GAGACGAGGGCGAUGAAUA 2149 CAUGAACCCUUCCUGGAUU 2150 NFKBIA GAACAUGGACUUGUAUAUU 2151 GAUGUGGGGUGAAAAGUUA 2152 GGACGAGAAAGAUCAUUGA 2153 AGGACGAGCUGCCCUAUGA 2154 NFKBIE GAAGGGAAGUUUCAGUAAC 2155 GGAAGGGAAGUUUCAGUAA 2156 GAAACUGCUGCUGUGUAC 2157 GAACCAACCACUCAUGGAA 2158 NUMA1 GGGAACAGUUUGAAUAUAA 2159 GCAGUAGCCUGAAGCAGAA 2160 CGAGAAGGAUGCACAGAUA 2161 GCAAGAGGCUGAGAGGAAA 2162 NUP153 GAAGACAAAUGAAAGCUAA 2163 GAUAAAGACUGCUGUUAGA 2164 GAGGAGAGCUCUAAUAUUA 2165 GAGGAAGCCUGAUUAAAGA 2166 OPA1 GAAAGAGCAUGAUGACAUA 2167 GAGGAGAGCUCUAUUAUGU 2168 GAAACUGAAUGGAAGAAUA 2169 AAAGAAGGCUGUACCGUUA 2170 PARVA CUACAUGUCUUUGCUCUUA 2171 GCUAAGUCCUGUAAGAAUA 2172 CAAAGGCAAUGUACUGUUU 2173 GAACAAUGGUGGAUCCAAA 2174 PIK3CG AAGUUCAGCUUCUCUAUUA 2175 GAAGAAAUCUCUGAUGGAU 2176 GAACACCUUUACUCUAUAA 2177 GCAUGGAGCUGGAGAACUA 2178 PRKDC AUGAAAGCUCUAAAGAUG 2179 AAAGGAGGUUCUAAACUA 2180 GAAGAAGCUCAUUUGAUU 2181 GCAAAGAGGUGGCAGUUAA 2182 RASA1 GGAAGAAGAUCCACAUGAA 2183 GAACAUACUUUCAGAGCUU 2184 GAACAAUCUUUGCUGUAUA 2185 UAACAGAACUGCUUCAACA 2186 SLC9A1 GAAGAGAUCCACACACAGU 2187 UCAAUGAGCUGCUGCACAU 2188 GAAGAUAGGUUUCCAUGUG 2189 GAAUUACCCUUCCUCAUCU 2190 TEGT CUACAGAGCUUCAGUGUGA 2191 GAACAUAUUUGAUCGAAAG 2192 GAGCAAACCUAGAUAAGGA 2193 GCAUUGAUCUCUUCUUAGA 2194 TERT GGAAGACAGUGGUGAACUU 2195 GCAAAGCAUUGGAAUCAGA 2196 GAGCUGACGUGGAAGAUGA 2197 GAACGGGCCUGGAACCAUA 2198 TNFRSF6 GAUACUAACUGCUCUCAGA 2199 GAAAGAAUGGUGUCAAUGA 2200 UCAAUAAUGUCCCAUGUAA 2201 UCAUGAAUCUCCAACCUUA 2202 GAUGUUGACUUGAGUAAAU 2203 TOP1 AAAGGAAAUGACUAAUGA 2204 AAGAAGGCUGUUCAGAGA 2205 GAAGUAGCUACGUUCUUU 2206 GACAUAAGUGGAAAGAAG 2207 TOP2A GAAAGAGUCCAUCAGAUUU 2208 CAAACUACAUUGGCAUUUA 2209 AAACAGACAUGGAUGGAUA 2210 CGAAAGGAAUGGUUAACUA 2211 TOP3A CCAGAAAUCUUCCACAGAA 2212 GAAACUAUCUGGAUGUGUA 2213 CCACAAAGAUGGUAUCGUA 2214 GGAAAUGGCUGUGGUAACA 2215 TOP3B GAGACAAGAUGAAGACUGU 2216 GCACAUGGGCUGCGUCUUU 2217 CCAGUGCGCUUCAAGAUGA 2218 GAACAUCUGCUUUGAGGUU 2219 WEE1 GGUAUUGCCUUGUGAAUUU 2220 GCAGAACAAUUACGAAUAG 2221 GUACAUAGCUGUUUGAAAU 2222 GCUGUAAACUUGUAGCAUU 2223

In addition, to identifying functional siRNA against gene families or pathways, it is possible to design duplexes against genes known to be involved in specific diseases. For example when dealing with human disorders associated with allergies, it will be beneficial to develop siRNA against a number of genes including but not limited to: the interleukin 4 receptor gene (SEQ. ID NO. 2224: UAGAGGUGCUCAUUCAUUU, SEQ. ID NO. 2225: GGUAUAAGCCUUUCCAAGA, SEQ. ID NO. 2412: ACACACAGCUGGAAGAAAU, SEQ. ID NO. 2226: UAACAGAGCUUCCUUAGGU), the Beta-arrestin-2 (SEQ. ID NO. 2227: GGAUGAAGGAUGACGACUA, SEQ. ID NO. 2228: ACACCAACCUCAUUGAAUU, SEQ. ID NO. 2229: CGAACAAGAUGACCAGGUA, SEQ. ID NO. 2230: GAUGAAGGAUGACGACUAU,), the interferon-gamma receptor 1 gene (SEQ. ID NO. 2231: CAGCAUGGCUCUCCUCUUU, SEQ. ID NO. 2232: GUAAAGAACUAUGGUGUUA, SEQ. ID NO. 2233: GAAACUACCUGUUACAUUA, SEQ. ID NO. 2234: GAAGUGAGAUCCAGUAUAA), the matrix metalloproteinase MMP-9 (SEQ. ID NO. 2235: GGAACCAGCUGUAUUUGUU, SEQ. ID NO. 2236: GUUGGAGUGUUUCUAAUAA, SEQ. ID NO. 2237: GCGCUGGGCUUAGAUCAUU, SEQ. ID NO. 2238: GGAGCCAGUUUGCCGGAUA), the Slclla1 (Nrampl) gene (SEQ. ID NO. 2239: CCAAUGGCCUGCUGAACAA, SEQ. ID NO. 2240: GGGCCUGGCUUCCUCAUGA, SEQ. ID NO. 2241: GGGCAGAGCUCCACCAUGA, SEQ. ID NO. 2242: GCACGGCCAUUGCAUUCAA), SPINK5 (SEQ. ID NO. 2243: CCAACUGCCUGUUCAAUAA, SEQ. ID NO. 2244: GGAUACAUGUGAUGAGUUU, SEQ. ID NO. 2245: GGACGAAUGUGCUGAGUAU, SEQ. ID NO. 2246: GAGC1JUGUCUUAUUUGCUA,), the CYP1A2 gene (SEQ. ID NO. 2247: GAAAUGCUGUGUCUUCGUA, SEQ. ID NO. 2248: GGACAGCACUUCCCUGAGA, SEQ. ID NO. 2249: GAAGACACCACCAUUCUGA, SEQ. ID NO. 2250: GGCCAGAGCUUGACCUUCA), thymosin-beta4Y (SEQ. ID NO. 2251: GGACAGGCCUGCGUUGUUU, SEQ. ID NO. 2252: GGAAAGAGGAAGCUCAUGA, SEQ. ID NO. 2253: GCAAACACGUUGGAUGAGU, SEQ. ID NO. 2254: GGACUAUGCUGCCCUUUUG, activin A receptor IB (SEQ. ID NO. 2255: ACAAGACGCUCCAGGAUCU, SEQ. ID NO. 2413: GCAACAGGAUCGACUUGAG, SEQ. ID NO. 2414: GAAGCUGCGUCCCAACAUC, SEQ. ID NO. 2256: GCAUAGGCCUGUAAUCGUA, SEQ. ID NO. 2257: UCAGAGAGUUCGAGACAAA, SEQ. ID NO. 2258: UGCGAAAGGUUGUAUGUGA, SEQ. ID NO. 2259: GCAACAGGAUCGACUUGAG, SEQ. ID NO. 2260: GAAUAGCGUUGUGUGUUAU, SEQ. ID NO. 2261: UGAAUAGCGUUGUGUGUUA, SEQ. ID NO. 2262: GGGAUCAGUUUGUUGAAUA, SEQ. ID NO. 2263: GAGCCUGAAUCAUCGUUUA,), ADAM33 (SEQ. ID NO. 2264: GGAAGUACCUGGAACUGUA, SEQ. ID NO. 2265: GGACAGAGGGAACCAUUUA, SEQ. ID NO. 2266: GGUGAGAGGUAGCUCCUAA, SEQ. ID NO. 2267: AAAGACAGGUGGCCACUGA), the TAP 1 gene (SEQ. ID NO. 2268: GAAAGAUGAUCAGCUAUUU, SEQ. ID NO. 2269: CAACAGAACCAGACAGGUA, SEQ. ID NO. 2270: UGAGAAAUGUUCAGAAUGU, SEQ. ID NO. 2271: UACCUUCACUCGAAACUUA, COX-2 (SEQ. ID NO. 2272: GAACGAAAGUAAAGAUGUU, SEQ. ID NO. 2273: GGACUUAUGGGUAAUGUUA, SEQ. ID NO. 2274: UGAAAGGACUUAUGGGUAA, SEQ. ID NO. 2275: GAUCAGAGUUCACUUUCUU), ADPRT (SEQ. ID NO. 2276: GGAAAGAUGUUAAGCAUUU, SEQ. ID NO. 2277: CAUGGGAGCUCUUGAAAUA, SEQ. ID NO. 2278: GAACAAGGAUGAAGUGAAG, SEQ. ID NO. 2279: UGAAGAAGCUCACAGUAAA,), HDC (SEQ. ID NO. 2280: CAGCAGACCUUCAGUGUGA, SEQ. ID NO. 2281: GGAGAGAGAUGGUGGAUUA, SEQ. ID NO. 2282: GUACAGAGCUGGAGAUGAA, SEQ. ID NO. 2283: GAACGUCCCUUCAGUCUGU), HnmT (SEQ. ID NO. 2284: CAAAUUCUCUCCAAAGUUC, SEQ. ID NO. 2285: GGAUAUAUCUGACUGCUUU, SEQ. ID NO. 2286: GAGCAGAGCUUGGGAAAGA, SEQ. ID NO. 2287: GAUAUGAGAUGUAGCAAAU), GATA-3 (SEQ. ID NO. 2288: GAACUGCUUUCUUUCGUUU, SEQ. ID NO. 2289: GCAGUAUCAUGAAGCCUAA, SEQ. ID NO. 2290: GAAACUAGGUCUGAUAUUC, SEQ. ID NO. 2291: GUACAGCUCCGGACUCUUC), Gab2 (SEQ. ID NO. 2292: GCACAACCAUUCUGAAGUU, SEQ. ID NO. 2293: GGACUUAGAUGCCCAGAUG, SEQ. ID NO. 2294: GAAGGUGGAUUCUAGGAAA, SEQ. ID NO. 2295: GGACUAGCCCUGCUGUUUA), and STAT6 (SEQ. ID NO. 2296: GAUAGAAACUCCUGCUAAU, SEQ. ID NO. 2297: GGACAUUUAUUCCCAGCUA, SEQ. ID NO. 2298: GGACAGAGCUACAGACCUA, SEQ. ID NO. 2299: GGAUGGCUCUCCACAGAUA).

In addition, rationally designed siRNA or siRNA pools can be directed against genes involved in anemia, hemophila or hypercholesterolemia. Such genes would include, but are not be limited to: APOA5 (SEQ. ID NO. 2300: GAAAGACAGCCUUGAGCAA, SEQ. ID NO. 2301: GGACAGGGAGGCCACCAAA, SEQ. ID NO. 2302: GGACGAGGCUUGGGCUUUG, SEQ. ID NO. 2303: AGCAAGACCUCAACAAUAU), HMG-CoA reductase (SEQ. ID NO. 2304: GAAUGAAGCUUUGCCCUUU, SEQ. ID NO. 2305: GAACACAGUUUAGUGCUUU, SEQ. ID NO. 2306: UAUCAGAGCUCUUAAUGUU, SEQ. ID NO. 2307: UGAAGAAUGUCUACAGAUA), NOS3 (SEQ. ID NO. 2308: UGAAGCACCUGGAGAAUGA, SEQ. ID NO. 2309: CGGAACAGCACAAGAGUUA, SEQ. ID NO. 2310: GGAAGAAGACCUUUAAAGA, SEQ. ID NO. 2415: GCACAAGAGUUAUAAGAUC), ARH (SEQ. ID NO. 2416: CGAUACAGCUUGGCACUUU, SEQ. ID NO. 2311: GAGAAGCGCUGCCCUGUGA, SEQ. ID NO. 2312: GAAUCAUGCUGUUCUCUUU, SEQ. ID NO. 2313: GGAGUAACCGGACACCUUA), CYP7A1 (SEQ. ID NO. 2314: UAAGGUGACUCGAGUGUUU, SEQ. ID NO. 2315: AAACGACACUUUCAUCAAA, SEQ. ID NO. 2316: GGACUCAAGUUAAAGUAUU, SEQ. ID NO. 2317: GUAAUGGACUCAAGUUAAA), FANCA (SEQ. ID NO. 2318: GGACAUCACUGCCCACUUC, SEQ. ID NO. 2319: AGAGGAAGAUGUUCACUUA, SEQ. ID NO. 2320: GAUCGUGGCUCUUCAGGAA, SEQ. ID NO. 2321: GGACAGAGGCAGAUAAGAA), FANCG (SEQ. ID NO. 2322: GCACUAAGCAGCCUUCAUG, SEQ. ID NO. 2323: GCAAGCAGGUGCCUACAGA, SEQ. ID NO. 2324: GGAAUUAGAUGCUCCAUUG, SEQ. ID NO. 2325: GGACAUCUCUGCCAAAGUC), ALAS (SEQ. ID NO. 2326: CAAUAUGCCUGGAAACUAU, SEQ. ID NO. 2327: GGUUAAGACUCACCAGUUC, SEQ. ID NO. 2328: CAACAGGACUUUAGGUUCA, SEQ. ID NO. 2329: GCAUAAGAUUGACAUCAUC), PIGA (SEQ. ID NO. 2330: GAAAGAGGGCAUAAGGUUA, SEQ. ID NO. 2331: GGACUGAUCUUUAAACUAU, SEQ. ID NO. 2332: UCAAAUGGCUUACUUCAUC, SEQ. ID NO. 2333: UCUAAGAACUGAUGUCUAA), and factor VIII (SEQ. ID NO. 2334: GCAAAUAGAUCUCCAUUAC, SEQ. ID NO. 2335: CCAGAUAUGUCGUUCUUUA, SEQ. ID NO. 2336: GAAAGGCUGUGCUCUCAAA, SEQ. ID NO. 2337: GGAGAAACCUGCAUGAAAG, SEQ. ID NO. 2338: CUUGAAGCCUCCUGAAUUA, SEQ. ID NO. 2339: GAGGAAGCAUCCAAAGAUU, SEQ. ID NO. 2340: GAUAGGAGAUACAAACUUU).

Furthermore, rationally designed siRNA or siRNA pools can be directed against genes involved in disorders of the brain and nervous system. Such genes would include, but are not be limited to: APBB1 (SEQ. ID NO. 2341: CUACGUAGCUCGUGAUAAG, SEQ. ID NO. 2342: GCAGAGAUGUCCACAGGUU, SEQ. ID NO. 2343: CAUGAGAUCUGCUCUAAGA, SEQ. ID NO. 2344: GGGCACCUCUGCUGUAUUG), BACE1 (SEQ. ID NO. 2345: CCACAGAGCAAGUGAUUUA, SEQ. ID NO. 2346: GCAGAAAGGAGAUCAUUUA, SEQ. ID NO. 2347: GUAGCAAGAUCUUUACAUA, SEQ. ID NO. 2348: UGUCAGAGCUUGAUUAGAA), PSEN1 (SEQ. ID NO. 2349: GAGCUGACAUUGAAAUAUG, SEQ. ID NO. 2350: GUACAGCUAUUUCUCAUCA, SEQ. ID NO. 2351: GAGGUUAGGUGAAGUGGUU, SEQ. ID NO. 2352: GAAAGGGAGUCACAAGACA, SEQ. ID NO. 2353: GAACUGGAGUGGAGUAGGA, SEQ. ID NO. 2354: CAGCAGGCAUAUCUCAUUA, SEQ. ID NO. 2355: UCAAGUACCUCCCUGAAUG), PSEN2 (SEQ. ID NO. 2356: GCUGGGAAGUGGCUUAAUA, SEQ. ID NO. 2357: CAUAUUCCCUGCCCUGAUA, SEQ. ID NO. 2358: GGGAAGUGCUCAAGACCUA, SEQ. ID NO. 2359: CAUAGAAAGUGACGUGUUA), MASS 1 (SEQ. ID NO. 2360: GGAAGGAGCUGUUAUGAGA, SEQ. ID NO. 2361: GAAAGGAGAAGCUAAAUUA, SEQ. ID NO. 2362: GGAGGAAGGUCAAGAUUUA, SEQ. ID NO. 2363: GGAAAUAGCUGAGAUAAUG,), ARX (SEQ. ID NO. 2364: CCAGACGCCUGAUAUUGAA, SEQ. ID NO. 2365: CAGCACCACUCAAGACCAA, SEQ. ID NO. 2366: CGCCUGAUAUUGAAGUAAA, SEQ. ID NO. 2367: CAACAUCCACUCUCUCUUG) and NNMT (SEQ. ID NO. 2368: GGGCAGUGCUCCAGUGGUA, SEQ. ID NO. 2369: GAAAGAGGCUGGCUACACA, SEQ. ID NO. 2370: GUACAGAAGUGAGACAUAA, SEQ. ID NO. 2371: GAGGUGAUCUCGCAAAGUU).

In addition, rationally designed siRNA or siRNA pools can be directed against genes involved in hypertension and related disorders. Such genes would include, but are not be limited to: angiotensin II type 1 receptor (SEQ. ID NO. 2372: CAAGAAGCCUGCACCAUGU, SEQ. ID NO. 2373: GCACUUCACUACCAAAUGA, SEQ. ID NO. 2374: GCACUGGUCCCAAGUAGUA, SEQ. ID NO. 2375: CCAAAGGGCAGUAAAGUUU, SEQ. ID NO. 2376: GCUCAGAGGAGGUGUAUUU, SEQ. ID NO. 2377: GCACUUCACUACCAAAUGA, SEQ. ID NO. 2378: AAAGGGCAGUAAAGUUU), AGTR2 (SEQ. ID NO. 2379: GAACAUCUCUGGCAACAAU, SEQ. ID NO. 2380: GGUGAUAUAUCUCAAAUUG, SEQ. ID NO. 2381: GCAAGCAUCUUAUAUAGUU, SEQ. ID NO. 2382: GAACCAGUCUUUCAACUCA), and other related targets.

Example XIII Validation of Multigene Knockout Using Rab5 and Eps

Two or more genes having similar, overlapping functions often leads to genetic redundancy. Mutations that knockout only one of, e.g., a pair of such genes (also referred to as homologs) results in little or no phenotype due to the fact that the remaining intact gene is capable of fulfilling the role of the disrupted counterpart. To fully understand the function of such genes in cellular physiology, it is often necessary to knockout or knockdown both homologs simultaneously. Unfortunately, concomitant knockdown of two or more genes is frequently difficult to achieve in higher organisms (e.g., mice) thus it is necessary to introduce new technologies dissect gene function. One such approach to knocking down multiple genes simultaneously is by using siRNA. For example, FIG. 11 showed that rationally designed siRNA directed against a number of genes involved in the clathrin-mediated endocytosis pathway resulted in significant levels of protein reduction (e.g., >80%). To determine the effects of gene knockdown on clathrin-related endocytosis, internalization assays were performed using epidermal growth factor and transferrin. Specifically, mouse receptor-grade EGF (Collaborative Research Inc.) and iron-saturated human transferrin (Sigma) were iodinated as described previously (Jiang, X., Huang, F., Marusyk, A. & Sorkin, A. (2003) Mol Biol Cell 14, 858-70). HeLa cells grown in 12-well dishes were incubated with ¹²⁵I-EGF (1 μg/ml) or ¹²⁵I-transferrin (1 μg/ml) in binding medium (DMEM, 0.1% bovine serum albumin) at 37° C., and the ratio of internalized and surface radioactivity was determined during 5-min time course to calculate specific internalization rate constant k_(e) as described previously (Jiang, X et al.). The measurements of the uptakes of radiolabeled transferrin and EGF were performed using short time-course assays to avoid influence of the recycling on the uptake kinetics, and using low ligand concentration to avoid saturation of the clathrin-dependent pathway (for EGF Lund, K. A., Opresko, L. K., Strarbuck, C., Walsh, B. J. & Wiley, H. S. (1990) J. Biol. Chem. 265, 15713-13723).

The effects of knocking down Rab5a, 5b, 5c, Eps, or Eps 15R (individually) are shown in FIG. 22 and demonstrate that disruption of single genes has little or no effect on EGF or Tfn internalization. In contrast, simultaneous knock down of Rab5a, 5b, and 5c, or Eps and Eps 15R, leads to a distinct phenotype (note: total concentration of siRNA in these experiments remained constant with that in experiments in which a single siRNA was introduced, see FIG. 23). These experiments demonstrate the effectiveness of using rationally designed siRNA to knockdown multiple genes and validates the utility of these reagents to override genetic redundancy.

Example XIV Validation of Multigene Targeting Using G6PD, GAPDH, PLK, and UQC

Further demonstration of the ability to knock down expression of multiple genes using rationally designed siRNA was performed using pools of siRNA directed against four separate genes. To achieve this, siRNA were transfected into cells (total siRNA concentration of 100 nM) and assayed twenty-four hours later by B-DNA. Results shown in FIG. 24 show that pools of rationally designed molecules are capable of simultaneously silencing four different genes.

Example XV Validation of Multigene Knockouts as Demonstrated by Gene Expression Profiling, a Prophetic Example

To further demonstrate the ability to concomitantly knockdown the expression of multiple gene targets, single siRNA or siRNA pools directed against a collection of genes (e.g., 4, 8, 16, or 23 different targets) are simultaneously transfected into cells and cultured for twenty-four hours. Subsequently, mRNA is harvested from treated (and untreated) cells and labeled with one of two fluorescent probes dyes (e.g., a red fluorescent probe for the treated cells, a green fluorescent probe for the control cells.). Equivalent amounts of labeled RNA from each sample is then mixed together and hybridized to sequences that have been linked to a solid support (e.g., a slide, “DNA CHIP”). Following hybridization, the slides are washed and analyzed to assess changes in the levels of target genes induced by siRNA.

Example XVI Identifying Hyperfunctional siRNA

Identification of Hyperfunctional Bcl-2 siRNA

The ten rationally designed Bcl2 siRNA (identified in FIG. 13, 14) were tested to identify hyperpotent reagents. To accomplish this, each of the ten Bcl-2 siRNA were individually transfected into cells at a 300 pM (0.3 nM) concentrations. Twenty-four hours later, transcript levels were assessed by B-DNA assays and compared with relevant controls. As shown in FIG. 25, while the majority of Bcl-2 siRNA failed to induce functional levels of silencing at this concentration, siRNA 1 and 8 induced >80% silencing, and siRNA 6 exhibited greater than 90% silencing at this subnanomolar concentration.

By way of prophetic examples, similar assays could be performed with any of the groups of rationally designed genes described in Example VII or Example VIII. Thus for instance, rationally designed siRNA sequences directed against

PDGFA

(SEQ. ID NO. 2383: GGUAAGAUAUUGUGCUUUA,

SEQ. ID NO. 2384: CCGCAAAUAUGCAGAAUUA,

SEQ. ID NO. 2385: GGAUGUACAUGGCGUGUUA,

SEQ. ID NO. 2386: GGUGAAGUUUGUAUGUUUA), or

PDGFB

(SEQ. ID NO. 2387: GCUCCGCGCUUUCCGAUUU,

SEQ. ID NO. 2388: GAGCAGGAAUGGUGAGAUG,

SEQ. ID NO. 2389: GAACUUGGGAUAAGAGUGU,

SEQ. ID NO. 2390: CCGAGGAGCUUUAUGAGAU,

SEQ. ID NO. 2391: UUUAUGAGAUGCUGAGUGA)

could be introduced into cells at increasingly limiting concentrations to determine whether any of the duplexes are hyperfunctional. Similarly, rationally designed sequences directed against

HIF1 Alpha

(SEQ. ID NO. 2392: GAAGGAACCUGAUGCUUUA,

SEQ. ID NO. 2393: GCAUAUAUCUAGAAGGUAU,

SEQ. ID NO. 2394: GAACAAAUACAUGGGAUUA,

SEQ. ID NO. 2395: GGACACAGAUUUAGACUUG), or

VEGF

(SEQ. ID NO. 2396: GAACGUACUUGCAGAUGUG,

SEQ. ID NO. 2397: GAGAAAGCAUUUGUUUGUA,

SEQ. ID NO. 2398: GGAGAAAGCAUUUGUUUGU,

SEQ. ID NO. 2399: CGAGGCAGCUUGAGUUAAA) could be introduced into cells at increasingly limiting concentrations and screened for hyperfunctional duplexes.

Example XVII Gene Silencing: Prophetic Example

Below is an example of how one might transfect a cell.

a. Select a cell line. The selection of a cell line is usually determined by the desired application. The most important feature to RNAi is the level of expression of the gene of interest. It is highly recommended to use cell lines for which siRNA transfection conditions have been specified and validated.

b. Plate the cells. Approximately 24 hours prior to transfection, plate the cells at the appropriate density so that they will be approximately 70-90% confluent, or approximately 1×10⁵ cells/ml at the time of transfection. Cell densities that are too low may lead to toxicity due to excess exposure and uptake of transfection reagent-siRNA complexes. Cell densities that are too high may lead to low transfection efficiencies and little or no silencing. Incubate the cells overnight. Standard incubation conditions for mammalian cells are 37° C. in 5% CO₂. Other cell types, such as insect cells, require different temperatures and CO₂ concentrations that are readily ascertainable by persons skilled in the art. Use conditions appropriate for the cell type of interest.

c. siRNA re-suspension. Add 20 μl siRNA universal buffer to each siRNA to generate a final concentration of 50 μM.

d. SiRNA-lipid complex formation. Use RNase-free solutions and tubes. Using the following table, Table XI: TABLE XI 96-well 24-well Mixture 1 (TransIT-TKO-Plasmid dilution mixture) Opti-MEM 9.3 μl 46.5 μl TransIT-TKO (1 μg/μl) 0.5 μl 2.5 μl Mixture 1 Final Volume 10.0 μl 50.0 μl Mixture 2 (siRNA dilution mixture) Opti-MEM 9.0 μl 45.0 μl siRNA (1 μM) 1.0 μl 5.0 μl Mixture 2 Final Volume 10.0 μl 50.0 μl Mixture 3 (siRNA-Transfection reagent mixture) Mixture 1 10 μl 50 μl Mixture 2 10 μl 50 μl Mixture 3 Final Volume 20 μl 100 μl Incubate 20 minutes at room temperature. Mixture 4 (Media-siRNA/Transfection reagent mixture) Mixture 3 20 μl 100 μl Complete media 80 μl 400 μl Mixture 4 Final Volume 100 μl 500 μl Incubate 48 hours at 37° C. Transfection. Create a Mixture 1 by combining the specified amounts of OPTI-MEM serum free media and transfection reagent in a sterile polystyrene tube. Create a Mixture 2 by combining specified amounts of each siRNA with OPTI-MEM media in sterile 1 ml tubes. Create a Mixture 3 by combining specified amounts of Mixture 1 and Mixture 2. Mix gently (do not vortex) and incubate at room temperature for 20 minutes. Create a Mixture 4 by combining specified amounts of Mixture 3 to complete media. Add appropriate volume to each cell culture well. Incubate cells with transfection reagent mixture for 24-72 hours at 37° C. This incubation time is flexible. The ratio of silencing will remain consistent at any point in the time period. Assay for gene silencing using an appropriate detection method such as RT-PCR, Western blot analysis, immunohistochemistry, phenotypic analysis, mass spectrometry, fluorescence, radioactive decay, or any other method that is now known or that comes to be known to persons skilled in the art and that from reading this disclosure would useful with the present invention. The optimal window for observing a knockdown phenotype is related to the mRNA turnover of the gene of interest, although 24-72 hours is standard. Final Volume reflects amount needed in each well for the desired cell culture format. When adjusting volumes for a Stock Mix, an additional 10% should be used to accommodate variability in pipetting, etc. Duplicate or triplicate assays should be carried out when possible.

While the invention has been described in connection with specific embodiments thereof, it will be understood that it is capable of further modifications and this application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departure from the present disclosure as come within known or customary practice within the art to which the invention pertains and as may be applied to the essential features hereinbefore set forth and as follows in the scope of the appended claims. 

What is claimed is:
 1. A kit for gene silencing, wherein said kit is comprised of a pool of at least two siRNA duplexes, each of which is comprised of a sequence that is complementary to a portion of the sequence of one or more target messenger RNA, and each of which is selected using selection criteria that are embodied in a formula comprising: selection criteria are embodied in a formula comprising: (−8)*A1+(−1)*A2+(12)*A3+(7)*A4+(18)*A5+(12)*A6+(19)*A7+(6)*A8+(−4)*A9+(−5)*A10+(−2)*A11+(−5)*A12+(17)*A13+(−3)*A14+(4)*A15+(2)*A16+(8)*A17+(11)*A18+(30)*A19+(−13)*U1+(−10)*U2+(2)*U3+(−2)*U4+(−5)*U5+(5)*U6+(−2)*U7+(−10)*U8+(−5)*U9+(15)*U10+(−1)*U11+(0)*U12+(10)*U13+(−9)*U14+(−13)*U15+(−10)*U16+(3)*U17+(9)*U18+(9)*U19+(7)*C1+(3)*C2+(−21)*C3+(5)*C4+(−9)*C5+(−20)*C6+(−18)*C7+(−5)*C8+(5)*C9+(1)*C10+(2)*C11+(−5)*C12+(−3)*C13+(−6)*C14+(−2)*C15+(−5)*C16+(−3)*C17+(−12)*C18+(−18)*C19+(14)*G1+(8)*G2+(7)*G3+(−10)*G4+(−4)*G5+(2)*G6+(1)*G7+(9)*G8+(5)*G9+(−11)*G10+(1)*G11+(9)*G12+(−24)*G13+(18)*G14+(11)*G15+(13)*G16+(−7)*G17+(−9)*G18+(−22)*G19+6*(number of A+U in position 15-19)−3*(number of G+C in whole siRNA),   Formula X wherein position numbering begins at the 5′-most position of a sense strand, and A₁=1 if A is the base at position 1 of the sense strand, otherwise its value is 0; A₂=1 if A is the base at position 2 of the sense strand, otherwise its value is 0; A₃=1 if A is the base at position 3 of the sense strand, otherwise its value is 0; A₄=1 if A is the base at position 4 of the sense strand, otherwise its value is 0; A₅=1 if A is the base at position 5 of the sense strand, otherwise its value is 0; A₆=1 if A is the base at position 6 of the sense strand, otherwise its value is 0; A₇=1 if A is the base at position 7 of the sense strand, otherwise its value is 0; A₁₀=1 if A is the base at position 10 of the sense strand, otherwise its value is 0; A₁₁=1 if A is the base at position 11 of the sense strand, otherwise its value is 0; A₁₃=1 if A is the base at position 13 of the sense strand, otherwise its value is 0; A₁₉=1 if A is the base at position 19 of the sense strand, otherwise if another base is present or the sense strand is only 18 base pairs in length, its value is 0; C₃=1 if C is the base at position 3 of the sense strand, otherwise its value is 0; C₄=1 if C is the base at position 4 of the sense strand, otherwise its value is 0; C₅=1 if C is the base at position 5 of the sense strand, otherwise its value is 0; C₆=1 if C is the base at position 6 of the sense strand, otherwise its value is 0; C₇=1 if C is the base at position 7 of the sense strand, otherwise its value is 0; C₉=1 if C is the base at position 9 of the sense strand, otherwise its value is 0; C₁₇=1 if C is the base at position 17 of the sense strand, otherwise its value is 0; C₁₈=1 if C is the base at position 18 of the sense strand, otherwise its value is 0; C₁₉=1 if C is the base at position 19 of the sense strand, otherwise if another base is present or the sense strand is only 18 base pairs in length, its value is 0; G₁=1 if G is the base at position 1 on the sense strand, otherwise its value is 0; G₂=1 if G is the base at position 2 of the sense strand, otherwise its value is 0; G₈=1 if G is the base at position 8 on the sense strand, otherwise its value is 0; G₁₀=1 if G is the base at position 10 on the sense strand, otherwise its value is 0; G₁₃=1 if G is the base at position 13 on the sense strand, otherwise its value is 0; G₁₉=1 if G is the base at position 19 of the sense strand, otherwise if another base is present or the sense strand is only 18 base pairs in length, its value is 0; U₁=1 if U is the base at position 1 on the sense strand, otherwise its value is 0; U₂=1 if U is the base at position 2 on the sense strand, otherwise its value is 0; U₃=1 if U is the base at position 3 on the sense strand, otherwise its value is 0; U₄=1 if U is the base at position 4 on the sense strand, otherwise its value is 0; U₇=1 if U is the base at position 7 on the sense strand, otherwise its value is 0; U₉=1 if U is the base at position 9 on the sense strand, otherwise its value is 0; U₁₀=1 if U is the base at position 10 on the sense strand, otherwise its value is 0; U₁₅=1 if U is the base at position 15 on the sense strand, otherwise its value is 0; U₁₆=1 if U is the base at position 16 on the sense strand, otherwise its value is 0; U₁₇=1 if U is the base at position 17 on the sense strand, otherwise its value is 0; U₁₈=1 if U is the base at position 18 on the sense strand, otherwise its value is
 0. 2. A method for selecting an siRNA, said method comprising: applying selection criteria to a set of potential siRNA that comprise 18-30 base pairs; and determining the relative functionality of the at least two siRNAs, wherein said section criteria are non-target specific criteria, said set comprises at least two siRNAs and each of said at least two siRNAs contains a sequence that is at least substantially complementary to a target gene, and said selection criteria are embodied in a formula comprising: (−8)*A1+(−1)*A2+(12)*A3+(7)*A4+(18)*A5+(12)*A6+(19)*A7+(6)*A8+(−4)*A9+(−5)*A10+(−2)*A11+(−5)*A12+(17)*A13+(−3)*A14+(4)*A15+(2)*A16+(8)*A17+(11)*A18+(30)*A19+(−13)*U1+(−10)*U2+(2)*U3+(−2)*U4+(−5)*U5+(5)*U6+(−2)*U7+(−10)*U8+(−5)*U9+(15)*U10+(−1)*U11+(0)*U12+(10)*U13+(−9)*U14+(−13)*U15+(−10)*U16+(3)*U17+(9)*U18+(9)*U19+(7)*C1+(3)*C2+(−21)*C3+(5)*C4+(−9)*C5+(−20)*C6+(−18)*C7+(−5)*C8+(5)*C9+(1)*C10+(2)*C11+(−5)*C12+(−3)*C13+(−6)*C14+(−2)*C15+(−5)*C16+(−3)*C17+(−12)*C18+(−18)*C19+(14)*G1+(8)*G2+(7)*G3+(−10)*G4+(−4)*G5+(2)*G6+(1)*G7+(9)*G8+(5)*G9+(−11)*G10+(1)*G11+(9)*G12+(−24)*G13+(18)*G14+(11)*G15+(13)*G16+(−7)*G17+(−9)*G18+(−22)*G19+6*(number of A+U in position 15-19)−3*(number of G+C in whole siRNA),   Formula X wherein position numbering begins at the 5′-most position of a sense strand, and A₁=1 if A is the base at position 1 of the sense strand, otherwise its value is 0; A₂=1 if A is the base at position 2 of the sense strand, otherwise its value is 0; A₃=1 if A is the base at position 3 of the sense strand, otherwise its value is 0; A₄=1 if A is the base at position 4 of the sense strand, otherwise its value is 0; A₅=1 if A is the base at position 5 of the sense strand, otherwise its value is 0; A₆=1 if A is the base at position 6 of the sense strand, otherwise its value is 0; A₇=1 if A is the base at position 7 of the sense strand, otherwise its value is 0; A₁₀=1 if A is the base at position 10 of the sense strand, otherwise its value is 0; A₁₁=1 if A is the base at position 11 of the sense strand, otherwise its value is 0; A₁₃=1 if A is the base at position 13 of the sense strand, otherwise its value is 0; A₁₉=1 if A is the base at position 19 of the sense strand, otherwise if another base is present or the sense strand is only 18 base pairs in length, its value is 0; C₃=1 if C is the base at position 3 of the sense strand, otherwise its value is 0; C₄=1 if C is the base at position 4 of the sense strand, otherwise its value is 0; C₅=1 if C is the base at position 5 of the sense strand, otherwise its value is 0; C₆=1 if C is the base at position 6 of the sense strand, otherwise its value is 0; C₇=1 if C is the base at position 7 of the sense strand, otherwise its value is 0; C₉=1 if C is the base at position 9 of the sense strand, otherwise its value is 0; C₁₇=1 if C is the base at position 17 of the sense strand, otherwise its value is 0; C₁₈=1 if C is the base at position 18 of the sense strand, otherwise its value is 0; C₁₉=1 if C is the base at position 19 of the sense strand, otherwise if another base is present or the sense strand is only 18 base pairs in length, its value is 0; G₁=1 if G is the base at position 1 on the sense strand, otherwise its value is 0; G₂=1 if G is the base at position 2 of the sense strand, otherwise its value is 0; G₈=1 if G is the base at position 8 on the sense strand, otherwise its value is 0; G₁₀=1 if G is the base at position 10 on the sense strand, otherwise its value is 0; G₁₃=1 if G is the base at position 13 on the sense strand, otherwise its value is 0; G₁₉=1 if G is the base at position 19 of the sense strand, otherwise if another base is present or the sense strand is only 18 base pairs in length, its value is 0; U₁=1 if U is the base at position 1 on the sense strand, otherwise its value is 0; U₂=1 if U is the base at position 2 on the sense strand, otherwise its value is 0; U₃=1 if U is the base at position 3 on the sense strand, otherwise its value is 0; U₄=1 if U is the base at position 4 on the sense strand, otherwise its value is 0; U₇=1 if U is the base at position 7 on the sense strand, otherwise its value is 0; U₉=1 if U is the base at position 9 on the sense strand, otherwise its value is 0; U₁₀=1 if U is the base at position 10 on the sense strand, otherwise its value is 0; U₁₅=1 if U is the base at position 15 on the sense strand, otherwise its value is 0; U₁₆=1 if U is the base at position 16 on the sense strand, otherwise its value is 0; U₁₇=1 if U is the base at position 17 on the sense strand, otherwise its value is 0; U₁₈=1 if U is the base at position 18 on the sense strand, otherwise its value is
 0. 3. A method according to claim 1, further comprising comparing the internal stability profiles of said at least two siRNAs.
 4. A method according to claim 2, further comprising comparing the internal stability profiles of said at least two siRNAs.
 5. A method according to claim 1, further comprising selecting either for or against sequences that contain motifs that induce cellular stress.
 6. A method according to claim 2, further comprising selecting either for or against sequences that contain motifs that induce cellular stress.
 7. A method according to claim 1, further comprising selecting either for or against sequences that comprise stability motifs.
 8. A method according to claim 2, further comprising selecting either for or against sequences that comprise stability motifs.
 9. A method of gene silencing, comprising introducing into a cell at least one siRNA selected according to a method of claim
 1. 10. A method of gene silencing, comprising introducing into a cell at least one siRNA selected according to a method of claim
 2. 11. A method according to claim 1, wherein said introducing is by allowing passive uptake of the at least one siRNA.
 12. A method according to claim 2, wherein said introducing is by allowing passive uptake of the at least one siRNA.
 13. A method according claim 9, wherein said introducing in through the use of a vector.
 14. A method for developing an siRNA algorithm for selecting siRNA, said method comprising: (a) selecting a set of siRNA; (b) measuring gene silencing ability of each siRNA from said set; (c) determining relative functionality of each siRNA; (d) determining improved functionality based on the following variables: the presence or absence of a particular nucleotide at a particular position, the total number of As and Us in positions 15-19, the number of times that the same nucleotide repeats within a given sequence, and the total number of Gs and Cs; and (e) developing an algorithm using the information of step (d).
 15. A method of selecting an siRNA with improved functionality, said method comprising using the algorithm of claim
 14. 16. A kit, wherein said kit is comprised of at least two siRNAs, wherein said at least two siRNAs comprise a first optimized siRNA and a second optimized siRNA, wherein said first optimized siRNA and said second optimized siRNA are optimized according a formula comprising: (−8)*A1+(−1)*A2+(12)*A3+(7)*A4+(18)*A5+(12)*A6+(19)*A7+(6)*A8+(−4)*A9+(−5)*A10+(−2)*A11+(−5)*A12+(17)*A13+(−3)*A14+(4)*A15+(2)*A16+(8)*A17+(11)*A18+(30)*A19+(−13)*U1+(−10)*U2+(2)*U3+(−2)*U4+(−5)*U5+(5)*U6+(−2)*U7+(−10)*U8+(−5)*U9+(15)*U10+(−1)*U11+(0)*U12+(10)*U13+(−9)*U14+(−13)*U15+(−10)*U16+(3)*U17+(9)*U18+(9)*U19+(7)*C1+(3)*C2+(−21)*C3+(5)*C4+(−9)*C5+(−20)*C6+(−18)*C7+(−5)*C8+(5)*C9+(1)*C10+(2)*C11+(−5)*C12+(−3)*C13+(−6)*C14+(−2)*C15+(−5)*C16+(−3)*C17+(−12)*C18+(−18)*C19+(14)*G1+(8)*G2+(7)*G3+(−10)*G4+(−4)*G5+(2)*G6+(1)*G7+(9)*G8+(5)*G9+(−11)*G10+(1)*G11+(9)*G12+(−24)*G13+(18)*G14+(11)*G15+(13)*G16+(−7)*G17+(−9)*G18+(−22)*G19+6*(number of A+U in position 15-19)−3*(number of G+C in whole siRNA),   Formula X wherein position numbering begins at the 5′-most position of a sense strand, and A₁=1 if A is the base at position 1 of the sense strand, otherwise its value is 0; A₂=1 if A is the base at position 2 of the sense strand, otherwise its value is 0; A₃=1 if A is the base at position 3 of the sense strand, otherwise its value is 0; A₄=1 if A is the base at position 4 of the sense strand, otherwise its value is 0; A₅=1 if A is the base at position 5 of the sense strand, otherwise its value is 0; A₆=1 if A is the base at position 6 of the sense strand, otherwise its value is 0; A₇=1 if A is the base at position 7 of the sense strand, otherwise its value is 0; A₁₀=1 if A is the base at position 10 of the sense strand, otherwise its value is 0; A₁₁=1 if A is the base at position 11 of the sense strand, otherwise its value is 0; A₁₃=1 if A is the base at position 13 of the sense strand, otherwise its value is 0; A₁₉=1 if A is the base at position 19 of the sense strand, otherwise if another base is present or the sense strand is only 18 base pairs in length, its value is 0; C₃=1 if C is the base at position 3 of the sense strand, otherwise its value is 0; C₄=1 if C is the base at position 4 of the sense strand, otherwise its value is 0; C₅=1 if C is the base at position 5 of the sense strand, otherwise its value is 0; C₆=1 if C is the base at position 6 of the sense strand, otherwise its value is 0; C₇=1 if C is the base at position 7 of the sense strand, otherwise its value is 0; C₉=1 if C is the base at position 9 of the sense strand, otherwise its value is 0; C₁₇=1 if C is the base at position 17 of the sense strand, otherwise its value is 0; C₁₈=1 if C is the base at position 18 of the sense strand, otherwise its value is 0; C₁₉=1 if C is the base at position 19 of the sense strand, otherwise if another base is present or the sense strand is only 18 base pairs in length, its value is 0; G₁=1 if G is the base at position 1 on the sense strand, otherwise its value is 0; G₂=1 if G is the base at position 2 of the sense strand, otherwise its value is 0; G₈=1 if G is the base at position 8 on the sense strand, otherwise its value is 0; G₁₀=1 if G is the base at position 10 on the sense strand, otherwise its value is 0; G₁₃=1 if G is the base at position 13 on the sense strand, otherwise its value is 0; G₁₉=1 if G is the base at position 19 of the sense strand, otherwise if another base is present or the sense strand is only 18 base pairs in length, its value is 0; U₁=1 if U is the base at position 1 on the sense strand, otherwise its value is 0; U₂=1 if U is the base at position 2 on the sense strand, otherwise its value is 0; U₃=1 if U is the base at position 3 on the sense strand, otherwise its value is 0; U₄=1 if U is the base at position 4 on the sense strand, otherwise its value is 0; U₇=1 if U is the base at position 7 on the sense strand, otherwise its value is 0; U₉=1 if U is the base at position 9 on the sense strand, otherwise its value is 0; U₁₀=1 if U is the base at position 10 on the sense strand, otherwise its value is 0; U₁₅=1 if U is the base at position 15 on the sense strand, otherwise its value is 0; U₁₆=1 if U is the base at position 16 on the sense strand, otherwise its value is 0; U₁₇=1 if U is the base at position 17 on the sense strand, otherwise its value is 0; U₁₈=1 if U is the base at position 18 on the sense strand, otherwise its value is
 0. 17. A method for identifying hyperfunctional siRNA, comprising: applying selection criteria to a set of potential siRNA that comprise 18-30 base pairs, wherein said selection criteria are non-target specific criteria, and said set comprises at least two siRNAs and each of said at least two siRNAs contains a sequence that is at least substantially complementary to a target gene; and determining the relative functionality of the at least two siRNAs and assigning each of the at least two siRNAs a functionality score; and selecting siRNAs from the at least two siRNAs that have a functionality score that reflects greater than 80 percent silencing at a concentration in the picomolar range, wherein said greater than 80 percent silencing endures for greater than 120 hours.
 18. A method according to claim 1, wherein said siRNA are unimolecular.
 19. A method according to claim 2, wherein said siRNA are unimolecular.
 20. A method according to claim 14, wherein said siRNA are unimolecular.
 21. A method according to claim 16, wherein said siRNA are unimolecular.
 22. A method according to claim 17, wherein said siRNA are unimolecular.
 23. A method according to claim 1, wherein said siRNA are comprised of two separate polynucleotide strands.
 24. A method according to claim 2, wherein said siRNA are comprised of two separate polynucleotide strands.
 25. A method according to claim 14, wherein said siRNA are comprised of two separate polynucleotide strands.
 26. A method according to claim 16, wherein said siRNA are comprised of two separate polynucleotide strands.
 27. A method according to claim 17, wherein said siRNA are comprised of two separate polynucleotide strands.
 28. A method according to claim 1, wherein said siRNA are expressed from one or more vectors.
 29. A method according to claim 2, wherein said siRNA are expressed from one or more vectors.
 30. A method according to claim 14, wherein said siRNA are expressed from one or more vectors.
 31. A method according to claim 16, wherein said siRNA are expressed from one or more vectors.
 32. A method according to claim 17, wherein said siRNA are expressed from one or more vectors.
 33. A method according to claim 1, wherein two or more genes are silenced by a single administration of siRNA.
 34. A method according to claim 2, wherein two or more genes are silenced by a single administration of siRNA.
 35. A method according to claim 14, wherein two or more genes are silenced by a single administration of siRNA.
 36. A method according to claim 16, wherein two or more genes are silenced by a single administration of siRNA.
 37. A method according to claim 17, wherein two or more genes are silenced by a single administration of siRNA.
 38. A kit according to claim 13, wherein one or more of said siRNA are unimolecular.
 39. A kit according to claim 13, wherein one or more of said siRNA are comprised of two separate polynucleotide strands.
 40. A kit according to claim 13, wherein one or more of said siRNA are capable of silencing the Bcl2 gene.
 41. A method for developing an siRNA algorithm for selecting functional and hyperfunctional siRNAs for a given sequence, comprising: (a) selecting a set of siRNAs; (b) measuring the gene silencing ability of each siRNA from said set; (c) determining the relative functionality of each siRNA; (d) determining the amount of improved functionality based on the following variables: the total GC content, melting temperature of the siRNA, GC content at positions 15-19, the presence or absence of a particular nucleotide at a particular position, relative thermodynamic stability at particular positions in a duplex, and the number of times that the same nucleotide repeats within a given sequence; and (e) developing an algorithm using the information of step (d). 